Quantifying Human Perfoi-mance Degradation in a Sliip Motion Environment: Experiments at tlie US Naval Biodynamics Laboratory.
P. Crossland (Defence Research Agency, U K )
J.L. Colwell (Defence Research Establishment Atlantic, Canada) A.E. Baltis (Naval Surface Warfare Center, Carderock Division, USA) F.D. Holcombe (Naval Biodynamics Laboratory, USA)
R. Strong (Institute of Naval Medicine, U K )
Abstract
This paper describes recent ship motion simulator experiments to examine the effects of ship motions on human performance. Volunteer navy personnel performed representative physical and cognitive tasks v/hile being exposed to simulated ship motions, derived f r o m a frigate in sea state five. The experiments were conducted in two phases at the US Naval Biodynamics Laboratory ( N B D L ) . Phase I examined motion induced interruptions ( M i l ) , which occur when ship motions cause a person to stumble or slide, and motion induced fatigue (MIF). Ttie goals for this phase were to provide empirical data f o r a mathematical model for predicting the occurrence of M i l s , and to determine i f an increase in energy expenditure due to ship motions could be reliably measured. Phase I I examined a variety of existing computer and paper based tests for assessing human cognitive and psychomotor performance. The goals for this phase were to identify reliable performance assessment tests for use at sea, and to obtain preliminary data on the sensitivity of various human abilities to ship motions. Also, data from Phase I I could be used for validation of a sea sickness, fatigue and performance assessment questionnaire developed for use during naval operations.
1. Introduction
The value of any method for assessing crew performance at sea depends upon the chosen
criteria. Currently, most criteria for naval operations are empirical, based upon experience with existing destroyers and frigates. A typical criterion for personnel operations on deck is that the root mean square (RMS) roil should not exceed four degrees. Qearly, the operations are not limited by the deck being inclined to four degrees; although occasional extreme inclinations to much greater angles can be limiting. In many cases, personnel operations are most limited by the lateral and vertical accelerations associated with these deck inclinations. Thus, it is inappropriate to use roll angle as the sole lateral motion criterion for deck operations. Using angular limits for criteria is especially misleading when assessing the operability of unconventional craft such as Small Waterplane Area Twin Hull (SWATH) ships or high speed marine vehicles. Tlie frequencies associated with the angular motions of the SWATH are generally lower than those observed on a conventional frigate and therefore result in lower accelerations on the SWATH. Conversely, the frequencies associated with high speed craft are much higher than those observed on a typical frigate, resulting in higher accelerations.
The series of ship motion simulator (SMS) experiments described here addresses particular aspects of human performance, with emphasis on motion induced interruptions and the effects of ship motions on cognitive performance. A motion induced interruption ( M i l ) occurs when the ship motions cause a person to lose balance by tipping or sliding. The general approach is to expose human subjects (volunteer US Naval personnel) to representative ship motions in the SMS. The effects of these motions on human performance are quantified by observing direct effects (e.g. the incidence of a stumble) and by measuring a variety of physiological parameters which may or may not have a direct cause/effect relationship with the motions (e.g. EKO heart rate).
2. Background
In 1989, an international workshop on Warship Operability was held at the Defence Research Establishment Atlantic ( D R E A ) to discuss seakeeping in ship design. A t this workshop, it was proposed that tho three participating nations (US, U K , and Canada) should join in a collaborative venture to sponsor a series of human factors experiments at the US Naval Biodynamics Laboratory (NBDL). This facility was chosen because of its resident expertise in human performance experimentation, and because it was the only ship motion simulator (SMS) with motion ranges sufficiently large (especially vertical motion) to be of practical use for this work. Subsequently, the Netherlands joined this
ad hoc working group, which adopted the title "ABCD working group on human
performance at sea" (ABCD = American, British, Canadian and Dutch). This working group consists of ship dynamics and human sciences researchers, who joined to create a
forum for information exchange, collaborative planning, and joint sponsorship of research and development on human performance at sea. The immediate application for this work is in the naval environment; however, most of this work will also be of use f o r civilian government and commercial applications.
The first major activity for the A B C D working group was to develop the programme of work which led to the human performance experiments described here. These experiments at N B D L were jointly funded by American, British, and Canadian naval research and slxip design agencies, while the Dutch contributed via ongoing exchange of information from their research prograrnme at the T N O Human Factors Research Institute, sponsored by the Royal Netherlands Navy. Information exchange between A B C D member agencies is accomplished under existing national memoranda of understanding.
3. . Tlieoretical Review
There are three critical ingredients for predicting the operational performance of any ship: a description of the environment in which it will operate; a method for predicting the ship's motions in response to the environment; and seakeeping criteria which establish the effects of these motions on the ship's operational performance.
Methods for describing the environment and calculafing ship motions are well established. Statistical data bases are available to describe the occurrence and severity of the waves in various locations (e.g. Juszko and Graham, 1992], and linear strip theory methods provide adequate ship motion predictions for operability assessment of conventional frigates and destroyers (e.g. Crossland, 1991]. Only recently has effort been devoted to establishing platform independent seakeeping criteria; in other words, criteria which are not based solely on experience with existing ships and ship systems.
A number of representative naval tasks "have been defined (Graham and Colwell, 1990], which describe in general terms how human performance can be quantified for the purpose of evaluating ship operability. This is a "top-down" approach, where it is hoped that generic measures of performance such as the M i l model, can be used for ship design trade off studies and for operational guidance. Conversely, the more detailed "bottom-up" approach must be used when analysing any specific real task, as is done for the cognitive performance experiment.
3.1 Motion Induced Interruptions ( M i l )
Baitis, Woolaver and Beck (1983] introduced the concept of motion induced interruptions ( M i l ) and developed the lateral force estimator (LFE) approach for estimating the occurrence of M i l s from lateral forces acfing on the person. Gniham [1990] extended this work to include both vertical and lateral accelerations, and to develop a model for the
frequency domain, whicli is better suited for use with contemporary strip theory methods. Non-zero vertical accelerations introduce asymmetry, and so two "generalized LFE" expressions are required, one for tipping to port, G L j , and the other for tipping to starboard, G L j
GL,
where, ^ is the roll angle and and are the lateral and vertical acceleration respectively (in fixed earth axes). The ratio / / / i is the "tipping coefficient", which represents the person's body geometry with vertical centre of gravity at h and one half stance width / , see Figure 1. A n analogous set of expressions is also developed for the body tipping frontwards and backwards, using one half shoe length d in place of /.
•r.
FtcingAA Roll Stbd Down
FoangAft Pilch Birw Dom»
Figure 1: Assumed M O mcxlci
Tlie generalized lateral force estimators can be calculated in the frequency domain by assuming they follow the Rayleigh distribution. From this, the number of M i l s expected during any particular span of time can be calculated, as follows.
GL •I naf
where. A/, is the number of M i l s (/ = 1 or 2 for tipping to port or starboard), Tj\^ the time span of interest (seconds), 7, is the zero crossing period of the generalised lateral force estimator.
for using the M i l model in seakeeping assessment [Graham, 1990]; however, tlus does not account for the human's ability to compensate for ship motion. The main goal for Phase I o f these N B D L experiments is obtain empirical tipping coefficient values fi-om observing real human performance in the simulator. It is expected that the human ability to "move with the ship", as well as the tendency to anticipate future motion will provide a more stable platform than the simple rigid body geometry would indicate and so, in effect, increase the tipping coefficient.
The M i l model was further refined to include an additional term to take account of the moment induced on the body by the rotational motion of the ship [Graham, Baitis and Meyers, 1992]. Tlie moment of ineriia of the person was esrimated by treadng the body as an ellipsoidal cylinder of height 2/i.
1 "
Tliis refinement gave an additional term of " ' " t ' both and D j
Other refinements made in this reference were to include the effects of steady and unsteady.winds; however, this extension is not explored in the current experiments. This work also proposed that seakeeping criteria should be presented in terms of limits on the occurrence of the degrading events which directly affect any particular operation, as opposed to more generic measures of overall ship motions. For example, instead of using criteria limits values for RMS pitch and roll angles, it is more useful to consider events such as the frequency of occurrence of M i l s (either tipping or sliding).
Under most conditions, M i l s associated with tipping occur before sliding becomes a problem; however, in some conditions (e.g wet deck), sliding problems may dominate. Graham, Baitis and Meyers [1991] describe a frequency domain method for estimating the incidence and severity of sliding, which includes the (linearized) forces due to roll, pitch, lateral and vertical accelerations, and also the effects of non-zero heel angle.
3.2 Cognitive performance
The M i l model describes a simple cause and effect relationship between the ship motions and the human's physical response; unfortunately, such simple models do not exist for "higher order" human cognitive and psychomotor functions. In the absence of a direct model, the following two step, indirect approach is used:
1. from ship motions, esfimate symptomatology; and, 2. from symptomatology, estimate performance,
where, "symptomatology " describes the presence and severity of the various symptoms produced by the ship motions.
symptoms are reviewed in Colwell [1989]. O'Hanlon and McCauley [1974] and McCauley
el al [1976] describe a model for predicting motion sickness incidence (MSI), from the
amplitude, frequency, and duration of exposure to vertical accelerations caused by ship motions. MSI is simply the percent of people who vomit when exposed to two hours of ship motions. Lawther and Griffin [1987] describe a method of calculating the vomiting incidence ( V I , analogous to MSI) using a 'dose' parameter which quantifies cumulative exposure to vertical accelerafions. In both cases, the link between M S I and vertical accelerations is empirical, in the same manner as traditional criteria based on ship roll and pitch motions. Tlie effects of other ship motions on MSI are not modelled, but the method should be adequate for most typical motions encountered in conventional frigates and destroyers. Efforts by various researchers to predict MSI in more complicated mofion environments (e.g. high speed vessels) have not been successful.
Lloyd and Andrew [1977] applied the MSI model to ship operations in rough weather. The accelerations were assumed to be distributed according to the Gaussian probability density to obtain an expression for the average acceleration. These approximations allowed the MSI formula to be used to make an estimate of the proportion of people who will suffer from seasickness in a given set of conditions at sea. Colwell [1994] introduced an empirical habituation function for use with the MSI model, which extends its application from the original short term exposures of only a few hours to longer exposures of many days, as encountered in the naval environment.
Methods for assessing motion sickness incidence, as described above, are a useful step towards predicting operability; however, as yet there are no means of relating motion sickness (or fatigue) to task performance. One method to obtain information on the effects of sea sickness (and other problems) on task performance is a questionnaire. The N A T O sea sickness, fatigue and performance assessment questionnaire (PAQ) [Colwell and Heslegrave, 1993] was developed for use during normal naval operations. The main purpose for the PAQ is to develop a large database on the incidence and severity of sea sickness and fatigue symptoms, and their perceived effects on human performance. The PAQ will also identify the presence and severity of performance problems related to M i l s and whole body vibration, but these are not the central focus. Once a sufficiently large database has been collected, it should indicate (for the first time) the general extent to which ship motion induced human performance problems exist during naval operations, and hopefully be a source for trend analysis to develop statistical estimators for relating sea sickness and fatigue symptomatology to performance degradation. The self assessment of performance, which is a central theme of the PAQ, is not validated; however, one objective of the Phase I I cognitive experiment described here is to provide preliminary data for this purpose. The main goals for the cognitive experiment are to investigate the effects of ship motions on human cognitive performance perse , and to develop validated
human performance tests for use at sea.
4. Test Facility
The N B D L Ship Motion Simulator (SMS) is located at the NASA Michoud Assembly Facility in New Orleans Louisiana, USA. The SMS consists of a cabin of cubical shape with sides of about 2.5 metres length, mounted on a roll and pitch motion actuator, which is in turn mounted on a large vertical motion platform.
Table 1 summarizes the motion capabilities of the SMS, and Figures 2 and 3 show schematic views of the SMS exterior and'interior floor plan.
Parameter Heave Pitch RoU
Displacement Velocity/rate Acceleration Usable bandwidth +-3.5 m +-5m/s +-0.9g 0.03 - 10 Hz +-15 degrees +-25 degs/s +-150 deg/s^ 0.06 -3.0 Hz +-15 degrees +-25 deg/s +-150 degs/s^ 0.06-3.0 Hz
Table 1: SMS System Capability
Visual and audio links between the interior of the cabin and the external control area allow continuous observation and communication with the subjects. A second, identical floor mounted cabin was used for the static control experiments. Tlie static and dynamic runs were balanced for order effects.
5. Summary of Experiments 5.1 M i l and Energy Expenditure
The goals for this phase of the experiment were to obtain empirical tipping coefficients for the M i l model described earlier, and to determine if increased energy expenditure caused by ship mofions could be reliably measured. There are two types of M i l s for which empirical tipping coefficients are required; body lateral (i.e. ripping sideways), and body longitudinal (i.e. tipping frontwards and backwards). O f these two cases, the lateral M i l is of greatest interest, as it models the natural stance taken when postural stability becomes compromised (e.g. the person is oriented sideways with respect to the predominant motion, in this case ship roll). During the experiment, while subjects are exposed to the simulated ship motions, the occurrence of each M i l was noted both by an independent observer (external to the SMS cabin), and verbally by the subject in the cabin. Empirical tipping coefficients are calculated after the fact by examining forces acting on the subjects at the time that each M i l occurred.
SCHEMATIC LOOKING FWD P O R T C A B I N T I L T -T A B L E MOVING . A - F H A M E H E A V E G U I D E • R A I L miwti G U I D E in/vu. nou. A X I S P I T C H A X I S S T B D
Figure 2: NBDL Sliip motion simulator
roiu
iiiiiiKbiïiiiiBilli
W t l q l i t B l : ! 4' (» R A *• 1 1 e L a r * « n K 1 1 e L (» H I I < 7 . 1 - > C a t a s r a »-K *• >In addition to the observed and reported M i l s , measurements taken during the experiment include: cabin motions, both input (or demand) signals and subsequent cabin motions; vertical and lateral accelerations at floor level in the centre of the cabin; subject referenced body accelerations using a triaxial accelerometer in a backpack worn by the subject; forces produced by the subject's feet from three force plates mounted flush with the centre óf the cabin floor; and, E K G heart rates. Also, three video cameras mounted inside the SMS cabin provided complete video records of the subject's stance throughout each experiment run. Each subject wore a tight fitting overall with video targets at the body's nominal centre of gravity and at major body joints. Also, during the pre-test pilot study performed to refine the siinulated ship mofion profiles, subjects wore special equipment for measuring oxygen consumption. Comparison of each subject's oxygen consumption between static and dynamic conditions provided the data on energy expenditure discussed later, but the equipment was considered too bulky for inclusion in the main experiment runs.
Sufficient information for calculating tipping coefficients is provided by the recorded SMS cabin motions and the M i l incidents themselves. The remaining parameters measured during the experiment will provide data for the possible future development of more detailed postural stability models, for either standing or more complex dynamic tasks. The video records were analysed to provide a single "snap-shot" view of each subject's real stance during each experiment run.
A total of fifteen human research volunteers (HRVs), all male USN personnel between the ages of 17 and 24, were used in this experiment. Each subject performed the following sequence of five physical tasks while exposed to two separate one hour simulated ship motion profiles:
1) standing facing 'astern' (2 minutes) - to observe body lateral M i l s caused while standing sideways with respect to the relatively large amplitude roll mofions;
2) weight posifioning task (1 minute) - the subject lifts a wciglit and slides it through a horizontal slot (a simplified model of a weapons loading task); 3) raised weight, standing facing astern ( I minute) - subject holds a weight
overhead, to observe the effect of a change in the centre of gravity position on body lateral M i l s . Due to safety considerations, the weight was a light weight styrofoam cylinder (0.6 kg, 15 cm diameter and 60 cm long) and so the change in CO was primarily due to the lifted arms.
4) walking (1 minute) - subject traverses the cabin (port/starboard), approximately three steps between turns; and,
5) standing facing to 'port' (1 minute) - to observe body longitudinal M i l s caused while standing facing towards the relatively large amplitude roll mofions.
This six minute sequence of tasks was repeated ten rimes during each experiment run. Instructions for changing between tasks were issued by a recorded script, synchronized witli the SMS motion control system. A n independent physician was present at all times who could (and on occasions did) terminate the experiment run due to concerns on the subject's well being, based either on visual observarions or the E K G records, or at the
I .
-subject's request.
Only the'standing tasks (1, 3 and 5) are related to die static M i l model, and only these tasks were located over the force plates mounted in the cabin floor. Tlie weight positioning aiid walking tasks were introduced to provide insight on the effects of M i l s on more complicated tasks (to determine if it may be possible to use equivalent static tipping coefficients to represent these complicated tasks), and to reduce the inevitable boredom associated with one hour of standing still in a moving simulator.
Two different simulated ship motion profiles were used, derived from predicted motions at the flight deck of a USN PTG7 class frigate in sea state five, with a ship speed of ten knots in short crested irregular seas with significant wave height of 3.25 metres and wave modal period of 10 seconds. One mofion profile represented bow seas (i.e. waves coming from 45 degrees off the bow) and the other represented stern quartering seas (designated Hotel and Lima, respectively). Tlie key difference between these motion conditions is tiie relative frequencies of the pitch and vertical motions; Hotel for the relatively high frequency bow seas, and Lima for the relatively low frequency following seas. Since roll motion transfer functions are relatively narrow banded (i.e. the ship only responds to a narrow range of wave frequencies), the roll frequencies are not much different for the two conditions.
Since the SMS cannot replicate lateral mofion, the gain of the SMS roll control signal was increased to promote the body lateral M i l s which were of highest interest. Pre-trial predictions using static tipping coefficients (based on body geometries) indicated that lateral M i l s would not be experienced until roll amplitudes approaching the SMS maximum capability of + / - fifteen degrees were experienced. Also, the pilot study indicated that mofion sickness became a problem for the unhabituated subjects, and so the vertical accelerafions were reduced by about twenty percent for the main experiment runs.
5.2 Cognitive Experiment
The primary goal for this phase of the N B D L experiments was to assess the effects of ship motions on human cognitive and psychomotor task performance (i.e. purely mental and mental/physical tasks); however, before this could be accomplished, the first step must be to validate the performance assessment tests themselves. A wide variety of candidate tests are regularly used to examine the effects of various stressors on human
perforraance (e.g. sleep deprivation, heat or cold, work load, etc.), but few have been used in a motion environment. Before any performance tests can be used in a new environment, it is important to validate them, as the new environment may affect the test, as well as affecting the human performing the test.
Thus, the cojgriitive experiment serves two purposes: (i) to begin development of a suite of performance assessment tests for use in a ship motion environment (real or simulated), and (ii) to provide insight into the effects of the ship motions on task performance, as measured by the tests. Additionally, the experiment will provide data f o r validating the subjective performance assessment approach used in the N A T O performance assessment questionnaire (PAQ), by allowing comparison of self rated perforraance with measured performance.
The general approach used in this experiment was to expose subjects to ship motions while performing a sequence of computer and paper based tests, including motion sickness and fatigue questionnaires (described later). A total of 48 volunteer US Naval personnel have each been exposed to four, 90 minute sessions in the SMS. The first session was primarily concerned with cognitive performance tests, and the second was primarily psychomotor tests (it was expected that a single, three hour session would promote an unacceptably high incidence of motion sickness). For each subject, the testing was spread over two days with a static and dynamic run of each day. The motion profile used for this experiment was based on the Hotel profile used in the M i l experiment, but not modified to increase roll and reduce vertical mofion. Each subject also performed an analogous training session in a static condition. The SMS cabins (both static and dynamic) were configured to hold two subjects, each seated at a computer workstation equipped with a keyboard, track ball, monitor and audio system. The subjects were separated by a partition and restrained by seat belts. Each subject wore a light weight, helmet mounted communication system. The prelimii;ary'experiment results presented later in this paper are only for the first 36 subjects, the results for the remaining subjects are not yet available, as the tests were completed very recently.
One of the most difficult problems associated with this experiment was selection of the performance assessment tests. It would be desirable to combine a variety of relatively pure, single ability tests with more complex tests which involve a variety of human abilities; however, no suitable complex tests could be identified. The complex tests which were considered either did not provide meaningful measurement capabilities, or they required too much training before the subjects reached a stable level o f performance. A set of suitable cognitive performance tests were developed using the abilities classificafion procedures, or taxonomy, due to Fleishman (Fleishman and Reilly,1992]. Fleishman's taxonomie approach is often used to develop human perforraance assessment test batteries. Tin's approach separates a complicated task into discrete components, and
identifies the individual human ability employed for each component. A total of 52 separate abilities are identified in the taxonomy, grouped into four categories; cognitive, psychomotor, gross body, and sensory (see Table A . I of Appendix A ) . One difficulty associated with this approach is combining results from individual ability tests to represent overall performance on a complex, real task; however, the insights provided by this approach are invaluable for idenfifying the relative importance of each ability. This approach was seen as the most practical choice for this work; but it is not the only approach. For example Wickens, [1984] multiple resource processing theory could have been used as an alternative.
For this experiment, the taxonomy approach was used to identify the abilifies required for maintaining ship posifion while performing replenishment at sea (RAS), also called underway replenishment (UNREP). This activity was chosen because it is a vital shipboard function that involves a wide variety of ship's personnel who employ a broad spectrum of abilities to accomplish their respective tasks. Task analysis indicated that this activity involves ten separate job categories: officer of the watch, signalman, helmsman, lee helmsman, after steersman, radar operator, electronics technician, rig operator(s), throtfieman, and oil king (or chief stoker). Each job was analysed and broken down into the required human abilities, and a provisional test battery for assessing these abilities was chosen for a pilot study. This paper summarizes the process used f o r test selection; future reports will document details of this work.
Initially, more than one test was selected for most abilities; however, in some instances only one test was deemed suitable, and in a few instances, no suitable test was identified. Test selection was based on the following criteria:
1) the test should be reliable;
2) a stJible score should be achievable;
3) the test must demonstrate construct validity (i.e. it should measure the ability for which it was designed) which should not be compromised by the mofion environment;
4) the test should not be too easy, nor too difficult (floor and ceiling effects); 5) it should not be susceptible to cheating or compromised by discussion
between subjects;
6) file test must have a history of previous use in stress research;
7) the test should be easy to administer and its results should be easy to score objectively;
8) the test should be easy for the subjects to understand;
9) it should be amenable to translation in a number of different languages; 10) for future considerations, the test should be widely available and reasonably
11) if computer based (which is desuable), the test should be easily portable and not require expensive special equipment.
Some of these criteria were evaluated in pre selection screening and others were evaluated during a pilot study (i.e. m the SMS). The final list of tests and abiUfies selected for^êhe main SMS experiment mcludes 31 tests for 20 different abilifies, as shown in Table A;2. This list represents those abilities judged most important f o r the RAS activity, which also had suitable tests available. Due to fime constraints, several abilifies had to be deleted which otherwise would be of interest, namely; problem sensifivi^, category flexibility, fluency of ideas, raathémafical reasoning, number facility, originality, and written comprehension.
Most tests were computer based; the subjects were trained to an asymptotic level before the experiments. Instructions for written tests were displayed on the performance assessment computer and, where required, verbal instructions were issued by computer audio track.
6. Discussion of Preliminary Results 6.1 Motion Induced Interruptions
There are two general approaches for calculating empirical tipping coefficients f r o m the M i l experiment: local analysis, where the forces acting on the subject at the time of each M i l are examined; and, global analysis, where the total number of M i l s observed are related to the overall motion environment. This summary of preliminary results considers only M i l s observed during static standing tasks 1 (body lateral M i l s ) and 5 (body longitudinal M i l s ) . Future publications will provide details on M i l s and empirical tipping coefficients for all five tasks.
The total number of M i l s observed during the experiment varied with the motion profile (Hotel or Lima), as shown in Table 2.
Hotel Lima
Body Lateral M i l s 88 30
Body Longitudinal M i l s 178 234
Table 2: Total Number of M i l s Observed
As expected, there were significantly more longitudinal M i l s than lateral, as the normal body posture provides least resistance against tipping frontwards and backwards. A perhaps unexpected trend is the discrepancy between motion profiles; for lateral M i l s ,
the Hotel motion profile produced the most events, whereas for longitudinal M i l s , the Lima mofion profile produced the most events.
Inspecfion of the local forces acting at the time of M i l events (i.e. local accelerafion vector expressed by the generalized lateral force esfimator, GL) led to the realization that different types o f M i l s had to be idenfified, as shown m Table 3. Also included in this table is the' total number of M i l s (for both types of M i l s in both mofion conditions) assodated with each category.
Type Description No. M i l s A M i l at or near smooth peak in GL 229
B M i l in opposite direction 8 C M i l at obvious disconfinuity in GL, 27
and not near peak
A C M i l at or near peak, but GL not smoofii 181
D M i l not explained by G L 31 E M i l too near start or end of task 22
(+2/-1 sec)
F M i l already identified for current GL peak 27
X other 5
Table 3: Classification of M i l types
The difference between these Mll.categories is in some cases qualitafive, and in other cases quantitative. The most important distincfion is between types A and AC, since the great majority o f events fall into one of these categories (69% f o r lateral and 8 1 % for longitudinal M i l s ) . For both A and A C types, the M i l occurred at or very near a peak in local forces acting on the subject: however, for the A type, the forces (or variafion of
GL with time) were smooth, or almost sinusoidal (typical of frigate motions); whereas for
the A C type, the forces were not smooth. Tlie question remains as whether a tip occurring at an A C peak (i.e not smooth) would have occurred if the peak had have been smooth. Two types of "unsmoothncss" could .be identified; one related to the irregularity of motions expected in a natural sej;.way and the other related to physical characterisfics of the SMS (i.e. at some times, it appeared that a high frequency oscillafion of the SMS cabin occurred unexpectedly). Since the distinction between a smooth and unsmooth peak is subjective, the M i l events were independently classified by two analysts, with very similar results. A l l empirical tipping coefficients discussed later are for the A and A C types combined. Other types of M i l s were not included in the analysis; but it is important to deal with them descriptively as they represent discarded data. Type B describe M i l s
that occur when there is no significant force acting on the subject in the direction o f interest, but there is in the opposite direction. For example, during task 1 when the subject is standing facing aft and generally experiencing large lateral motions from roll, then type B describes the M i l s which occur when there was no significant lateral force, but there is>a peak in longitudinal force (i.e. the subject likely tipped frontwards or backwards); This ambiguity could be resolved by examining video records. Type C describea M i l s which occur at times when the local forces acting on the subject are not large, but the forces change in an "unpredictable" way (e.g the subject anticipated one type of motion but a different one occurred). This suggests that the mechanism producing the M i l is related to the subject's anticipation of future motion, which may be an important and separate mechanism to consider for future work. Tlie type D M i l is one that occurs during relatively quiescent periods, when the SMS cabin is barely moving. I t is possible that the subject's attention wandered, or that some other mechanism was acting (e.g. motion sickness symptoms). Type E describes those M i l s that occurred very near to the start or end of a task (i.e. just after or before changing tasks); these M i l s are discarded as the subject was likely to be still changing tasks. The net effect of discarding these M i l s is to ignore the first and last motion cycle in each task. The type F M i l occurs when more than one tip or stumble is caused by (or associated with) a single peak in local forces. A typical situation is where the subject regains his balance for a brief period, but then stumbles again during a single motion cycle. Since the M i l model can only predict the number of events per motion cycle, type F M i l s should not be counted (although they may indicate that the M i l was especially severe). Finally, the type X M i l is used to classify all events not described by the preceding types. A typical type X M i l is one which occurs after the SMS motions have stopped, but before the entire experiment protocol has finished (as happened a few times in runs terminated due to growing motion sickness symptoms in the subject). In this case, the M i l was formally reported by either the subject or observer, but it is not interest for the current M i l model.
Table 4 summarizes the results for tipping coefficients calculated using both the local and global analysis approaches; these represent the average of all the subjects. The differences between body lateral and body longitudinal tipping coefficients are as expected. The lower values for body longitudinal tipping coefficients indicate, as expected, that this type of M i l occurs at lower levels of force than the body lateral M i l (i.e a person is less stable when standing facing into the primary lateral force than when standing at right angles to it). Differences between motion conditions for the same type of M i l are not great and may lie within experimental error; however, in three of the four cases, the tipping coefficient is greater in the Lima profile than its equivalent in the Hotel profile. Tliis may indicate that the subjects can anticipate or react more easily in the relatively low
frequency profile. Tliis further suggests a possible frequency dependence for the fipping coefficient, which is not incorporated in the M i l model.
•} Lateral M i l s Longitudinal M i l s | Local Analysis Hotel Profile Local Analysis Hotel Profile 0.235 0.185 Lima Profile 0.229 0.200 Global Analysis Hotel Profile 0.288 0.204 Lima Profile 0.294 0.221
Table 4: Empirical Tipping Coefncients
Figure 4 shows both tipping coefficients for each subject plotted on an arbitrary scale of height of the subjects centre of gravity; the figure gives an indication of the spread of the data. There appears to be very little spread in the longitudinal tipping coefficient in the local analysis, which is rather encouraging. There is more spread in the calculation of the body lateral tipping coefficient (for both global and local analysis). A point to note is the number of subjects who did not experience any body lateral M i l s (without exception all subjects experienced body longitudinal M i l s ) . Three subjects did not experience lateral M i l s in the Hotel profile and 5 in the Lima profile. Therefore, the variability in the lateral tipping coefficient is not fully defined by these experiments.
6.2 Energy Expenditure Preliminary Results
Energy expenditure was investigated during the M i l experiment pilot study by measuring subjects' oxygen consumption while performing the sequence of M i l tasks. This interest in energy expenditure is due to the likely association between the accumulation of effects of work done by altering posture to compensate for ship motions and the development of motion induced fatigue, M I F . Other likely mechanisms for the development of fafigue in prolonged exposure to ship motions may be related to the quanfity and quality of rest and sleep, as affected by motion sickness symptoms, and/or by the physical effects of the motions themselves. These long term effects cannot be examined in the relatively short experiment runs used in these experiments.
Figure 5 uses a bar chart format to summarize the energy expenditure results for the eight subjects tested (the numbers correspond to subject identification codes). Two bars are used for each subject; the unshaded bar represents energy consumption in the static condition (i.e. cab not moving), and the shaded bar shows the corresponding measurement in the moving SMS.
Local Analysis: Lateral Mils (Standing Facing Stern) =0.'3 9-0.2 5
- * '
A • He * •\ ' t
• •
1 * 'ÏV
* 1 * • • 0.1 1 1 1 1 1Global Analysis: Lateral Mils (Standing Facing Stern) 1 ^ '
*
1 ± • -. a 4 l i n n ' '•
•
-- • Hotel - . A Lima ^ No Mlis 1 1 1 1Local Analysis: Longitudinal Mils (Standing Facing Port) 0.31 * 0 . 2 0.1 - 1 ' 1 ' 1 '
-
•
1 . 1 • 1 1 ' 0.95 1.00 1.05 1.10 1.15Height to Centre of Gravity (m) Figure 4: Sample Tipping (Coefficients
For comparative purposes, the right most bar shows the equivalent energy expenditure for walking on level ground at a pace of about 2 miies/hr (3.2 km/lu). I t is clear that the subjects expended more energy in the motion environment; however, the amount of extra energy expended is relatively small.These results are encouraging, as they suggest that measuring oxygen consumption is a reliable (or at least consistent) method f o r examining the effects jOf ship motions on energy expenditure. It is reasonable to expect that greater differenoes between static and moving conditions would be found for longer term exposures, and for more severe motion profdes as commonly encountered in smaller vessels. 2 O.ft 0.5 -0.4 0.3 0.2 -OA n
1
I 1 S t » B c TTZi Motion 3Sr 262 260 2 3 2 256 261 251 259 3 u b i « c ( NuroborFigure 5: Energy expenditure
6 J Cognitive Experiment Preliminary Results
Table A.3 summarizes preliminary results for the first 36 subjects in the cognitive experiments.
A significance test was carried out on the results of the test battery in the static and dynamic conditions. The details of the test are shown in Appendix A . The significance test is based upon the null hypothesis that the means of the results from both conditions are the same. The significance level is the size of the test for which the null hypothesis is just rejected; any smaller size and it would not. The value p, shown in some of the tables is often used to suggest how strong the evidence is in favour of the alternative hypothesis,' i.e that the means are different.
A subjective conversion between the p-values and a verbal statement of the weight of evidence is as follows :
p < 0.001 very strong evidence of difference between motion conditions p < 0.010 strong evidence
p < 0.025 fairly strong evidence p < 0.050 some evidence p < 0.100> slight evidence p > 0.10Ó no real evidence.
So, f o r example, a value of p < 0.001 is very strong evidence to suggest a difference between in the static and motion conditions.
In general, the effects of motions on task performance (from a point of view of exercising an ability) can be summarised as follows
Motion Energy expended Motion sickness Direct effects Arousal Fatigue -Task Performance
Fatigue was not a problem during this nominal 90 minute test period performing cognitive tasks while seated, as the associated energy expenditure should be low.
In general, the direct effects of motions on different categories of human abilities can be ranked in order of sensitivity to motions as follows:
Mechanical ( M i l ) Most effect Psychomotor
Visual
Purely cognitive least/no effect
The main study indicates that for relatively short exposures to motions, purely cognitive skills are not degraded. Test involving psychomotor skills revealed more significant differences. Arousal effects appear significant; one observation made during the main study of the cognitive experiments was that once volunteers were being recruited from sources external to N B D L the motion sickness incidence of all subjects became zero. Tliis indicates the strong influence that attitude and expectation may have on behaviour. The results of the motion sickness questionnaires must be interpreted with caution in the light of such observations. Similarly, where there are significant differences observed Ln cognitive or psychomotor performance, and M S I is also noticeably different, it will be important to ascertain whether task performance is similarly influenced by attitude change i.e where attitudes are such as to suppress motion sickness symptomalogy, are there also beneficial effects on performance?
6.4 Questionnaire Preliminary Results
Two questionnaires were administered during both the M i l and cognitive experiments. Tlie N A T O sea sickness, fatigue and performance a.ssessment questionnaire (PAQ) [Colwell and Heslegrave, 1993] was administered near the end of each experiment run, but while thö SMS was shll in motion. Results for the PAQ have not yet been analysed. In addition, a subset of the N B D L motion sickness questionnaire (MSQ) was administered during the runs, and preliminary results are discussed below.
Tlie MSQ checklist, shown in Table B . l of Appenduc B, consists of 25 questions. Nine responses to the questions are based on the four point Likert scale; 15 are simple yes/no items, the final question is not scored.
Table B.2 shows the results of administering the Checklist to subjects during the M i l study. The table shows the difference between the pre-test and post-test results in the dynamic condition.
The Student's t-test revealed no significant differences in post-test means of the overall questionnaire in dynamic and static conditions; however, each motion condition there were significant differences between the pre-test and post-test means. For the purpose of evaluating subjective symptomatology, each item on the Checklist was compared individually. Tlie most reliable indicators of motion sickness appear to be those most commonly associated with nausea. There were significant differences between the post-test means of dynamic and static motion conditions for:
General discomfort Boredom Drowsiness Fullness of head Increased salivation Stomach awareness Nausea
And, as shown in Table B.3, within the dynamic group there was strong-evidence (p < 0.01) to suggest differences in the means of the pre-test and post-test in the dynamic condition for:
General discomfort Drowsiness
Headache Nausea
and fairly strong evidence (p < 0.025) to suggest differences in the means of the pre-test and post-test in the dynamic condition for:
Increased salivation Voraifing
Note that the subjects were withdrawn from tlie motion simulator when significant mofion qrmptoms became apparent, and so the incidence of vomiting observed is lower than might be expected. One would expect a significant difference (p < 0.001) between stafic and d)mamic conditions for vomifing, if all experiment runs were extended to the full one hour duration.
The MSQ results mdicate that the symptoms of motion sickness were more apparent in the M i l istudy (Table B.2) than the cognitive study (Table B.2). There were a higher number of p's < 0.001 in the M i l study than the cognitive study. This is probably due to the higher angular motions experienced'in the M i l study (despite the fact the M S I calculations are based entirely on vertical accelerations). It could also be due to the differences in the level of activity experienced in both studies. In the cognitive study, the seated subjects were occupied in performing demanding tasks. In the M i l study the subjects had long periods of standing around doing nothing. Perhaps the lack of a comparable need to concentrate on the task in hand has led to an increase in symptoms of motion sickness?
7. Conclusions
This paper has described a set of unique experiments to quantity the effects of ship motions on the crew performance. Data from these experiments will be valuable for validafion of postural stability models. A significant amount of data has yet to be analysed and will be the subject of further work.
The M i l model proposed by Graham, [1990] has been validated to some extent. Both global and local analysis have found empirical values for the ripping coefficients; values that are not significantly different from those proposed by Graham, [1990).
However, limitations in the maximum roll and pitch morion capability of the N B D L simulator, and especially in the absence of lateral motion and yaw, have compromised the realism of the morion histories used in Phase I of the experiments. I t is likely that the lack of pure linear lateral motion is the primary cause for the unexpectedly low incidence (an in some cases the complete lack) of body lateral M i l s .
Further experimental work is planned at a motion simulator at the Defence Research Agency ( D R A ) Bedford, U K . This simulator can replicate ship morions in five degrees of freedom (i.e all motions except surge). So, it can be used to obtain lateral fipping coefficients f o r the M i l model in completely realistic conditions (in frigates, surge accelerations are usually significantly lower than other motions
Phase I I of the N B D L experiments have successfully identified a cognitive test battery f o r use (or at least to be partly used) in further tests of this nature. The study has shown that for relatively short exposures to mofions purely cognitive skills are not degraded; tests involving psychomotor skills revealed some differences.
Further experimental work is also planned for the motion simulator at the T N O Human Factors Research Institute, The Netherlands. Tliis work will pay particular attention to to the effects of energy expenditure on motion induced fatigue in a higher frequency motion environment (i.e small boat motions). The work will also examine cognitive and psychomotor task performance effects for significantly longer exposures to motions (from 4 to 6 hours).
Further work concerning Phase I I of the work could be to validate the performance tests battery by comparison with real task perfonnance at sea, and simultaneously to evaluate the potential of the N A T O Performance Assessment Questionnaire [Colwell and Heslegrave, 1993) as an alternative and more simply administered means of assessing performance at sea.
It is possible to factor analyse the results of the questionnaires. Characteristically, two primary factors can be extracted, one associated with fatigue and boredom, and one associated directly with sickness and other motion sickness symptoms. In view of the significant pre- and post-test differences in the questionnaire responses, but non significant mofion comparison, a further analysis could be conducted to elucidate these experimental findings.
Acknowledgements
This project was supported by the Procurement Execufive, Ministry of Defence, Canadian Department of National Defence and the United States Department of the Navy. © Copyright 1994. United States Department of the Navy; Copyright 1994. Department of National Defence Canada for Her Majesty the Queen; British Crown Copyright 1994 /MOD. Published with the permission of the Controller of Her Britannic Majesty's Stationery Office.
References
A E Baitis, D A Woolaver, T A Beck. Rudder RoU Stabilisation for Coast Guard Cutters
and Frigates. Naval Engineers Journal 1983.
A C Bittner, J C Guignard. Human Factors Engineering Principles for Minimising Adverse
Ship Motion Effects: Theory and Practice. Naval Engineers Journal, V o l 97, No.4 1985.
J L Colwell. Human Factors in the Naval Environment: A Review of Motion Sickness and fl/Wynfl/mc/Vo6/mw. D R E A Technical Memorandum 89/220. September 1989. Unlimited Distribution.
J L Colwell, R J Heslegrave. Seasickness, Fatigue and Peifomiance Assessment
Questionnaire. D R E A Report 93/105. September 1993. Unlimited Distribution
J L Colwell. Motion Sickness Habituation in the Naval Environment., D R E A Teclmical Memoranduhi 94/211. May 1994. Unlimited Distribution.
f
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P Crosslarid. User Guide for tlie PAT-91 Suite of Ship Motion Computer Programs. DRA/Mar/rR91316. September 1991.
E A Fleishman, M E Reilly. Handbook of Human Abilities: Definitions, Measurements and
Job Task Requirements. Palo Alto, CA: Consulting Psychologists Press, Inc. 1992.
R Graham. Motion Induced Interruptions as Ship Operability Criteria. Naval Engineers Journal, Vol 102, No. 2, March 1990.
R Graham, A E Baitis, W G Meyers. A frequency Domain Method for Estimating the
Incidence and Severity of Sliding D T R C Report SHD-1361-01. August 1991.
R Graham, A E Baitis, W G Meyers. On the Development of Seakeeping Criteria. Naval Engineers Journal. May 1992.
R Graham, J L Colwell. Assessing the Effects of Ship Motions on Human Performance:
Standard Tasks for the Naval Environment. N A T O Working Paper
AC/141(IEG/6)SG/5-WP/15, November 1990
J F O'Hanlon, M E McCauley. Motion Sickness Incidence as a Function of Frequency and
Acceleration of Vertical Sinusoidal Motion. Aerospace Medicine 1974.
B A Juszko, R Graham. Development of a Statistical Wave Climate Description Based on
10-Parameter Spectra. 3rd International Workshop on Wave Hindcasting and Forecasting.
Montreal, May 1992.
A Lawther, M J Griffin. Prediction of the Incidence of Motion Sickness fi-om the Magnitude,
Frequency and Duration of Vertical Oscillation. Journal of the Acoustical Society of
America. 82(3). September 1987.
A R J M Lloyd, R N Andrew. Criteria for Ship Speed in Rough Weather. 18th American Towing Tank Conference. Vol.2 August 1977.
M.E. McCauley, J.W. Royal, J.E. Shaw, and L.O. Schmitt, Motion Sickness Incidence;
Exploratory Studies of Habituation, Pilch and Roll, and lite Refinement of a Matltematical Model, Human factors Research inc.. Technical Report 1733-2 , April 1976.
C D Wickehs. The structure of attenlional resources. R Nickerson ed. Attention and perforraancL, V o l 3. Englewood Qiffs, New Jersey. Pubhshed by Erlbaum. pp239-257
APPENDIX Ai PHASE U , COGNITIVE EXPERIMENT TABLES
Ability Type* Ability Type
L Oral Comprehension C 27. Finger Dexterity P
2. Writtet»' Comprehension
3. Oral Expression
C 28. Wrist-Finger Speed P
2. Writtet»' Comprehension
3. Oral Expression c 29. Speed of Limb Movement P
4. Written Expression c 30. Selective Attention P
5. Fluency of Ideas c 31. Time Sharing P
6. Originality c 32. Static Strength B
7. Memorization c 33. Explosive Strength B
8. Problem Sensitivity c 34. Dynamic Strength B
9. Mathematical Reasoning c 35. Trunk Strength B
10. Number Facility c 36. Extent Flexibility B
11. Deductive Reasoning c 37. Dynamic Flexibility B
12. Inductive Reasoning c 38. Gross Body Coordination B
13. Information Ordering c 39. Gross Body Equilibrium B
14. Category Flexibility c 40. Stamina B
15. Speed of Closure c 41. Near Vision S
16. Flexibility of Qosure c 42. Far Vision S
17. Spatial Orientation c 43. Visual Colour Discrimination S
18. Visualisation c 44. Night Vision S
19. Perceptual Speed c 45. Peripheral Vision S
20. Control Precision p 46. Depth Perception S
21. Multilimb Coordination p 47. Glare Sensitivity S
22. Response Orientation p 48. General Hearing S
23. Rate Control p 49. Auditory Attention S
24. Reaction Time p 50. Sound Localisation S
25. Arm-Hand Steadiness p 51. Speech Hearing S
26. Manual Dexterity • n n . ' t . " . . - • ^ p 52. Speech Clarity S C - Cognitive P - Psychomotor B - Gross Body S - Sensory
Human Ability Name of Test Oral comprehension Watson-Barker Listening lest Written expression ETS Controlled Association
ETS Figure of Speech
tr. —
Memorization
i i . { :•
WRPAB Pattern Comparisons I & U WRPAB Digit Recall
TNO Taskomat
Deductive reasoning CCAB Logical Relations WRPAB Logical Relations Inductive reasoning ETS Letters Sets
CCAB Missing Items Information ordering Following Directions Speed of closure ETS Gestalt Completion
ETS Concealed Words Flexibility of closure ETS Hidden Figures
ETS Hidden Patterns Spatial orientation ETS Card Rotation
O M P A T Match to Sample Visualisation ETS Paper Folding Test
Surface Development Perceptual speed ETS Number Comparison
ETS Finding A's
Control precision A N A M Pursuit Tracking
Response orientation WRPAB Four Choice Reaction Time
Rate control WRPAB Time Wall
Reaction time Simple Reaction Time
Manual dexterity Minnesota Rate Manipulation Test Finger dexterity Purdue Pegboard
A r m hand steadiness Lafayette steadiness tester hole Multilimb coordination Lafayette 2 arm coordination Wrist-finger speed Tapping Board
Ability Static ' Dynamic T-test Test N Mean SD N Mean SD P Deductive reafoning
C C A B Locical relations WRPAB JLoRical relations
36 35 1285.7 -18,8 167.6 1.6 32 32 1275.6 48.6 1822 2 0 >0.1 > 0.1 Rcxibility offdosure
ETS^ Hidden figures E T S Hidden' patlcms 36 36 57.3 6 0 4.4 21.8 35 35 4.4 58.4 4.0 24.2 <0.1 > 0.1 Inductive* reasoning -C -C A B Missing items E T S Letter sets 36 36 1354.9 10.0 151.9 2,4 32 35 1396.0 10.0 163.2 2 3 >0.1 > 0.1 Information ordering E T S Following direction 36 6 6 2.1 35 6.7 23 >0.1 Memorization
WRPAB Digit rccaU
W R P A B Pattern comparison 1 W R P A B Pattern comparison 11 34 36 36 6 7 8.0 7.6 1 2 1.5 1.4 32 32 32 6 5 7.2 7.7 2 0 1.5 1.5 >0.1 < 0.025 > 0.1 Oral comprehension
Watson Barker listening test 36 19.2 4.8 32 19.0 4.9 > 0.1 Perceptual speed E T S Hnding A's E T S Number Comparison 36 36 31.1 14.5 10.2 4.3 32 33 29.6 129 10.1 4.3 > 0.1 < 0.1 Spatial orientation
OMPAT match to sample ETS card rotations
35 36 10.0 61.1 Z4 14.6 33 32 9.1 58.8 24 167 < 0.1 > 0.1 Speed of closure E T S concealed words
ETS Cieslalt completion 36 36
14.9 7.4 4.0 1.4 33 32 13.7 6 9 3.1 1.5 < 0.1 < 0.1 Time Sharing
ETS paper folding ETS Surface development
36 36 5.1 16.5 23 8.1 33 34 167 5.3 2 2 9.3 > 0.1 > 0.1 Wriltcnexpression E T S Controlled associations E T S Figures of speech 36 36 15.7 10.0 8.2 3.2 34 33 15.6 10.1 8.5 3.0 > 0.1 > 0.1 Control precision
ANAM Pursuit tracking 36 10.1 8.4 33 11.1 11.7 > 0.1 Rate Control
WRPAB Time wall 36 61 2.7 32 6.4 3.3 > 0.1 Reaction time
STRES Simple reaction time 36 201.5 62.3 33 192.2 69.6 >-0.1 Response orientation
WRPAB Oioice reactjon time
WRPAB Choice reaction time accuracy 35 35 48.9 6 3 1.1 1.4 32 32 61 48.7 1.0 2 0 > 0.1 > 0.1 Ami hand steadiness
Lafayette steadiness tester 34 56.1 27.4 33 85.6 40.8 < 0.001 Finger dexterity
Purdue pegboard right band Purdue pegboard left hand Purdue pegboard both hands Purdue pegboard assembly
36 35 36 36 17.0 16.8 24.0 9.7 28 24 8.0 1.6 29 33 33 33 17.0 17.0 220 9.2 3.8 24 7.1 1.7 > 0.1 > 0.1 > 0.1 > 0.1 Manual dexterity
minnesota rate manipulation 36 32.1 65 34 33.4 7.6 > 0.1 Multilimb coordination
Lafayette 2-ann coordination clockwise Lafayette 2-arm coordination
anticlockwise
Lafayette 2-ami coord, clockwise time Lafayette 2-arm coord, anticlockwise time 36 36 36 36 1.3 1.0 30.8 25.0 2.7 1.5 15.3 13.8 32 33 32 33 2.4 2 3 365 26.1 3.2 28 18.4 13.6 > 0.1 < 0.025 < 0.1 > 0.1
Wrist fineer speed Tapper board right hand
Tapper board left hand 36 36 78.3 81.1
13.2 11.1 28 30 80.9 76.2 20.4 18.3 > 0.1 > 0.1 Table A J : Phase I I Cognitive Experiment Main study, preliminary results.
APPENDIX B: M O T I O N SICKNESS Q U E S l l O N N A I R E
ANSWER THIS WHETHER O N WATCH OR NOT
SYMPTOMATOTOGY CHECKLIST - H O W Y O U F E E L N O W
I-1. Genöral Discomfort none [ ] slight [] moderate [] severe [ ] 2. Fatigue none [ ] slight [ ] moderate [] severe [ ] 3. Boredom. none [ ] slight [] moderate [] severe [ ] 4. Mental depression no [] yes []
5. Drowsiness none [J slight [] moderate [] severe [] 6. Headache none [ ] slight [] moderate [] severe [] 7. Fullness of head no [] yes []
8. Blurred Vision no [] yes []
9. Dizziness with eyes open no [] yes []
10. Dizziness with eyes closed no [] yes [] not tried [ ]
11. Salivation INCREASED none [ ] slight [] moderate [ ] severe [ ] 12. Salivation U N U S U A L no [] yes []
13. Salivation DECREASED none [ ] slight [] moderate [ ] severe [ ] 14. Sweating none [ ] slight [] moderate [] severe []
15. Faintness no [] yes [ ] 16. Aware of breathing no [] yes [] 17. Stomach Awareness no [] yes []
18. Nausea none [ ] slight [] moderate [ ] severe [] 19. Burping no [] yes [] No. of times
20. Confusion " no (] yes [] 21. LOSS of appetite no [] yes [ ]
22. INCREASED appetite no [] yes [] 23. Desire to move bowels no [] yes [] 24. Vomiting no [] yes []
25. OTHER...(describe) :
Symptom Pre-test (dynamic)
mean SD
Post-test (dynamic) T-test
W mean SD 1. General discomfort 2. Fatigu^*' 3. Boredom 4. Mental depression 5. Drowsiness 6. Headache 7. Fullness of head 8. Blurred vision
9. Dizziness with eyes open 10. Dizziness with eyes closed 11. Salivation increased 12. Salivation unusual 13. Salivation decreased 14. Sweating 15. Faintness 16. Awareness of breathing 17. Stomach Awareness 18. Nausea 19. Burping 20. Confusion 21. Loss of appetite 22. Increased appetite 23. Desire to move bowels 24. Vomiting 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 0.083 0.083 0.083 0.056 0.167 0.194 0.167 0.000 0.028 0.000 0.000 0.333 0.000 0.083 0.028 0.139 0.111 0.056 0.000 0.000 0.028 0.056 0.083 0.000 0.368 0.280 0.280 0.232 0.447 0.525 0.378 0.000 0.167 0.000 0.000 0.478 0.000 0.368 0.167 0.351 0.319 0.333 0.000 0.000 0.167 0.232 0.280 0.000 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 0.694 0.833 0.528 0.083 0.583 0.694 0.250 0.056 0.139 0.111 0.417 0.472 0.000 0.833 0.111 0.333 0.444 0.722 0.361
Qsm
0.222 0.056 0.056 0.028 0.822 0.811 0.941 0.280 0.841 0.786 0.439 0.232 0.351 0.398 0.732 0.506 0.000 0.941 0319 0.478 0.504 0.914 0.487 0.000 0.422 0.232 0.232 0.167 < 0.001 < 0.001 < 0 . 0 1 > 0.1 < O.OI < 0.01 > 0.1 < 0.1 < 0.025 < 0 . 1 < 0.001 > 0.1 < 0.001 < 0.1 < 0.05 < 0.001 < 0.001 < 0.001 < 0.01 > 0.1 > 0 . I > O.ISymptom Pre-test (dynamic) Post-test (dynamic) T-test N mean SD N mean SD P 1. Genera? discomfort i 49 0.082 0.344 39 0.462 0.790 <0.01 , e 2. Fatigue 49 0.061 0.242 39 0.256 0.637 < 0.05 3. Boredom 49 0.102 0.306 39 0.282 0.686 < 0.1 4. Mental depression 49 0.000 0.000 39 0.000 0.000
-5. Drowsiness 49 0.061 0.243 39 0.462 0.756 < 0.01 6. Headaclie 49 0.082 0.277 39 0.410 0.677 < O.OI 7. Fullness of head 49 0.122 0.331 39 0.282 0.456 < 0.05 8. Blurred vision 49 0.020 0.143 39 0.077 0.270 > 0.1 9. Dizziness with eyes open 49 0.000 0.000 39 0.051 0.223 < 0.1 10. Dizziness with eyes closed 49 0.041 0.200 39 0.103 0.307 > 0.1 11. Salivation increased 49 0.020 0.143 39 0.256 0.637 < 0.025 12. Salivation unusual 49 0.082 0.277 39 0.051 0.223 > 0.1 13. Salivation decreased 49 0.000 0.000 39 0.026 0.160 > 0.114. Sweating
-
-
-
-
-
-
-15. Faintness 49 0.020 0.143 39 0.051 0.223 > 0.1
16. Awareness of breathing 49 0.102 0.306 39 0.077 0270 > O.I 17. Stomach Awareness 49 0.184 0.391 39 0.308 0.468 < 0.1 18. Nausea 49 0.163 0.373 39 0.641 0.903 < 0.01 19. Burping 49 0.082 0.277 39 0.205 0.409 < 0.1 20. Confusion 49 0.000 0.000 39 0.000 0.000
-21. Loss of appetite 49 0.041 0.200 39 0.051 0.223 > 0.1 22. Increased appetite 49 0.061 0.242 39 0.026 0.160 > 0.1 23. Desire to move bowels 49 0.041 0.200 39 0.103 0.307 > 0.124. Vomiting 49 0.000 0.000 39 0.128 0.339 < 0.025
Table B J Phase 11 Cognitive Experiment- Symptomatology Checklist, Summary of Results
