Assessing the effects of L F E stabilisation on human perFormance
I
P Crossland, A J Hiomas (Defence Research Agency) R Strong Gnstitute of Naval Medicine)
Abstract
At present, most warships in the Royal Navy are stabilised for roll using active fin stabilisers. This type of stabilisation has been of great value in enhancing the operational effectiveness of warships in rough weather. In a conventional system, the roll angle, roll velocity and roll acceleration signals derived from the roll gyro on board ship are used to control the fins. However, recent research has suggested that the crew performance is degraded by apparent acceleration in the plane of the deck (lateral force estimator or LFE) rather than roll. Tliis has led to the idea of using fins to control and reduce LFE.
This paper represents a multi-disciplinary effort between the ship hydrodynamics and human factors conununities to assess tlie feasibility of LFE stabilisation by evaluating the results o f human performance experiments at sea. The performance of 18 members of a ships company was compared for three modes of stabilisation (unstabilisedi roll and LFE stabilised). The volunteers carried out three tasks in calm water, and repeated them three times in rough weather under each mode of stabilisation.
The results of the trial indicated significant differences in perfonnance between calm water and rough weather trials, but no significant difference between modes of stabilisation. Great experience in undertaking and collating the results of human performance experiments was gained from carrying out these trials. The results of the experiments have led to the development of a probabilistic approach to predicting disturbances to the smooth conduct of human biomechanical tasks known as motion induced interruptions (Mils).
Notation
Symbol Meaning Units
g Acceleration due to gravity m/s/s GLi,„ RMS generalised lateral force estimator m/s/s
h Height of person's CG above the decic metres ! Half of tlie widths of a persons stance metres Mi ( Number of M i l ' s as a result of GLi
N„ I / Total number of Mils Np Total number of Ctlp pealcs
5 „ Lateral acceleration relative to body axes m/s/s Sgj Vertical acceleration relative to body axes m/s/s
52 Lateral acceleration relative to earth m/s/s
53 Vertical acceleration relative to earth m/s/s
Mean of vertical acceleration relative to earth m/s/s
T t Time required to complete task seconds Tou Zero crossing period of GLi seconds x Longitudinal distance from CG to accelerometer position metres
y Transverse distance from CG to accelerometer position metres
y Sway acceleration mlsls z Vertical distance from CG to accelerometer m/s/s
a „ Measured rms f i n angle degs a Mean rms fin angle degs cT^ RMS Ctip
RMS of CTip peaks causing an M i l
4» Roll angle rads 4)^ Corrected rms roll angle rads
Measured roll angle rads 4» Roll acceleration rads/s/s % Yaw acceleration rads/s/s (i> Frequency rads/s/s
1. Background
In rough weather the effectiveness o f a ship is degraded by excessive motions, slamming, decIc wetness and other undesirable phenomena. These combme to ensure tliat the crew's ability to operate and mamtain various ship systems is degraded. In extreme conditions the motions may be so severe that the crew wpl have to devote much of theh energy and attention to "hanging on" and avoiding personal mjury,rather than paying attention to the task in hand.
It has been sHown that the motions which have an immediate effect on a man's ability to move around the ship in a controlled and coherent manner are the local vertical and apparent lateral accelerations at the man's location in the ship. The apparent lateral acceleration in the plane of the ship's deck (including the component due to gravity when tlie ship is rolled) has been termed tlie Lateral Force Estimator (LFE) because it is an indicator of the force which tends to make objects and men slide or topple (i.e suffer a motion induced interruption or MR) when motions are excessive.
If LFE and vertical accelerations are excessive the crew will have to hang on all the time and the task will take longer or may not be completed at all.
Current practice on Royal Navy (and other) ships is to use the fin stabilisers to reduce roll motion. This is justified by the fact that many ship systems are sensitive to roll and their performance is improved i f roll is reduced. There is also little doubt that reducing roll motion generally improves the habitability of the ship and makes life easier for the crew. However it seems likely that habitability and crew performance could be ftirtlier improved by using the fins to control LFE instead of roll angle. One of the major attractions of LFE stabilisation is that existing fin systems with minor modifications would be employed.
It is envisaged that a future stabiliser system might have the options of selecting roll stabilisation during roll sensitive operations or LFE stabilisation when the crew are required to complete some particularly important task. LFE stabilisation would be selected for the appropriate part of the ship. This paper investigates the feasibility and desirability of LFE stabilisation by assessing the results Of some human factors experiments undertaken on a sea trial.
2 Review
LFE stabilisation is an old concept. In the past the idea has been explored under the name of stabilisation to the apparent vertical. Despite the satisfactory performance of active stabilisers to restrict roll motions, LFE has importance when assessing the performance of the crew. The desire to stabilise a ship for LFE stems from the wish to provide a more stable platform which would enhance ship operability.
Tlie naval design community has long recognised the need for objective and reliable data on the effects of ship motions on the ability of the crew to complete their allotted tasks effectively . Severe ship motion limits the ability of the crew to operate weapon and sensor systems and to carry out routine shipboard activities. It is essential at the design stage to quantify performance degradation.The three critical steps to predicting operational performance of ships are: a description of the environment
in wliich the sliip will operate; a method of predictmg the response; and seakeepmg criteria to evaluate the effects of ship motions on performance.
Data based on environmental conditions provide statistical descriptions of many operational areas such as [Bales, Lee and Voelker, 1989] using various methods such as hmdcastiog as shown by [Juszko, Graham, I992J.r5trip theory provides a useful tool for predictmg Ihe motions of a ship (Andrew, Loader and Penn, 1984].
However, l e ^ effort has been devoted to establishing rational seakeeping criteria.
An important step forward m the development of rational seakeeping criteria was the introduction of the lateral force estimator. The concept of lateral force estunator (LFE) was introduced by [Baitis, Woolaver and Beck, 1983] as being a combination of the ship's (earth reference) lateral accelerations and apparent lateral acceleration due to ship roll as shown m Figure I.
/ \ ms^-mg(f-cos^ J
Figure 1: Apparent forces on an object on the deck.
The reference also applied levels of risk to limits of LFE based upon the number of Mils. An M i l occurs when local motions cause a person to lose balance or slide, and so interrupt tlie task in hand. Hence, the concept of Mils is of value to the ship design community by providing a useful tool for assessing operational performance. [Graham, 1990] showed that LFE could be calculated in the frequency domain using
Some modifications were made in [Graham, Baitis and Meyers,1992]. To assess the feasibility of LFE stabilisation, an investigation was set up based upon numerical models and sea trials. It was conjectured that by utilising existing algorithms for roll stabilisation an LFE stabiliser system could
be numerically modelled. [Tang, Wilson, 1992] found encouraging r^ults from numerical work by using the fms to stabilise for LFE. One aspect from this work that was made clear was the need to design a new controller to stabilise for LFE; also having designed a new controller the correct timing of that controller is important. So, tuning a L F ^ stabilisation system at the natural roll frequency was not as effective as the roll system itself. A logical extension of usmg the fins to control LFE was to undertake numerical studies into using the rudders for LFE stabilisation (RLS). Intuitively, as the rudders are l(icated near the flight deck, good motion control at this position could be expected. So, RLS was investigated numerically by [Tang, Wilson, 1992] but found to be less effective.
3 L F E stabilisation at sea
LFE stabilisation with fins was first attempted in December 1992. In these experhnents the motion and fin responses were recorded when the ship was roll stabilised, LFE stabilised and unstabilised. The results of these trials are reported by [Tang, Crossland and Wilson, 1993]. Unformnately, the sea state was not sufficient to create considerable ship motions and tlie results were inconclusive. Nevertheless, the ship was stabilised for LFE without any undesirable effects. The trials had to be repeated at a later date. [Tang et al,l993] gives a detailed assessment of the f i n system and the hardware interface to the fin controller; also discussed is the tuning procedure adopted for the trials which were to follow.
Much international effort is currently being devoted to establishing criteria for human performance at sea. In support of this international program of work, human factors trials were carried out by DRA Alverstoke and the Institute of Naval Medicine. The primary aim of these experiments was to assess the effects of different modes of ship stabilisation on tlie performance on a number of simple tests. Additional objectives were to gain experience in carrying out human factors experiments of this type and to increase the human performance database.
The trial was carried out off the West coast of Scotland. Rough weather was encountered after leaving the Firth of Clyde and heading out throu£.h the North Channel towards tlie North Atlantic. This trials position meant that the wave conditions were dominated by a heavy swell from the West/Northwest. The trials were carried out in what was jirobably a locally generated sea state 3-with a very regular swell superimposed on it. This meant that the ship motions were predictable.
The human factors trials were aimed at evaluating the effects of the different modes o f stabilisation on various aspects of human performance and activity. The experiments consisted of three separate practical components:
a) Task T, tapping task, cairied out by the Institute of Navaj Medicine,
b) Task P, postural stability task, carried out by the Institute of Naval Medicine, c) Task E, exercise task, carried out by DRA Life Sciences Division.
Eighteen subjects completed each of the three tasks once only in calm water; to use as a baseline measurement. Tliey also completed a motion sickness history questionnaire and the 'Experiences Today' questionnaire.
The same eighteen subjects were allocated to one of six groups. Each group of three were required for approximately one hour. During this time each subject completed the three tasks three tunes (m each motion condition).
The purpose of the tapping task, task T, was to assess fine psycho-motor skills while making ballistic (unsupported) hpid and arm movements. This task was based upon the 'Spoke' and 'Aunmg* tests of [Fleishman, Ellison, 1962] which were demonstrated by [Guignard.Bittner and Carter, 1982] to be sensitive to the effects o f vibration. Subjects were given a sheet of A4 paper with 35 targets linked by a series of zig-zag lines, as shown in Figure 2.
bUBJECT; I SET MO:
Figure 2: Tapping Task
The subject was instructed to work their way around the page following the lines and marking the centre of the target with a felt tip pen. Each subject was told to perform this task as quickly and accurately as possible; no contact was allowed between the desk and any part of the body. The test sheets were taped to the desk. Accuracy was indicated by tlie distance between the pen mark and the centre of each target; a distance of 2mm or less was considered a hit. The total time taken to complete the task was also recorded. An indictor was used to electronically mark the start and end of the task. Each subject was required to complete the task twice under each mode of stabilisation, the first acting as a practice session with these results being excluded from the analysis.
The purpose of the postural stability task, P, was to assess the types and amount of gross body movement shown by subjects in attempting to maintain their balance and avoid an MIL Each subject was fitted with a series of seven reflective markers as shown in Figure 3; an eighth marker was
placed on the deck as a reference marker.
I . .Hight SIrauliicr
I
-Figure 3: Marker position
The subjects were asked to adopt a comfortable standing position facing aft over the ship's centre line. Each subject was requested to place the inside edge of each foot on a chalk line that was about 18 cms to either side of the centre line of the ship. Subjects were then requested to maintain their posture whilst being videoed for two minutes. An electronic indicator was used to mark the start and end o f the recording period and any Mils occurring during the recording period. An M i l occurred whenever the subjects moved their feet to prevent themselves falling over. The recorded MIL was based on when the observer perceived an M i l to have occurred.
The videotape of each subject at each condition was digitised using a motion analysis system. To ensure that the subject was settled the section of videotape used began at least 15 seconds into the task. In addition, care was taken to avoid using a section of videotape that contained Mils as this would have caused irregular and unrepresentative marker movement.
The following data were collected from the digitisation of the videotape:
a) The maximum displacement in centimetres (maximum position minus minimum position) of markers in both the Y (lateral) axis and the Z (vertical) axis of movement.
from ttiis the maximum and average lateral speed of each marker.
c) The variation in the angle subtended from a I'me through the shoulder markers (line H in Figure 3) and the horizontal.
d) The variation in the angle subtended between a line from the stemum to the floor laarker Qine V in Figure 3) and the vertical.
e) (The number of Mils experienced by each subject.
The energy expenditure experiment was based on the prmciple that oxygen uptake and ventilation rate are related to the production of metabolic energy. It was proposed that under different exercise conditions, ie calm water, rough water with and without stabilisers, that the amount of energy expended on a task conunon to all conditions would reflect the difficulty of maintaining performance. Ventilation volume is primarily determined by the level of exercise being undertaken, the response is driven by the need to maintain arterial p O j , p C O j , and pH. Where tlie '.p* means partial pressure of oxygen, carbon dioxide and hydrogen respectively.
The ventilation response is largely determined by the need for CO2 to be exchanged from the blood to the inspired air in the alveolar structures of the lung. In healthy individuals the mean alveolar PO^ and PCOj are equal to those in the arterial blood. Arterial pH is maintained by regulation of arterial PCOj. In steady state conditions the rate of exchange equals the rate o f production in tlie body tissues. This has been derived by experiment and the relationship shown below
V^(BTPS)= 863 VCOj(STPD)/PCOj (2) During steady state exercise, the rate of pulmonary CO^ clearance and the rate of tissue CO^
production are a function o f the work rate, the work efficiency and the energy substrate mixture undergoing oxidation. The degree of work efficiency is related to the muscle groups involved, and is thus task specific see [Whipp and Wasserman, 1969], the leg muscles are generally more efficient than the arm muscles at equivalent work rates. The steady state level of COj clearance is affected by the energy substrate utilised. In aerobic conditions both fat and carbohydrate metabolism yield COj and HjO as end products, the rate of oxygen iiptake and carbon dioxide output is shown as
C ^ , A + 6 0 j : - 6 C 0 , + 6H2O + 36ATP (3) I f fats are utilised as an energy source, COj is produced as
CifiHjzOj + 230^ - 16C0j + 16HjO + 130ATP (4) It can be seen that fat metabolism yields slightly less energy per molecule of oxygen than
carbohydrate, in a ratio o f 6:5.6. The ratio of oxygen to carbon dioxide is known as the Respiratory Quotient (RQ) , thus the RQ will be I for only carbohydrate metabolism and 0.7 for fat metabolism. Usually both fiiels are used concurrently,, resulting in an RQ of 0.85.
In non-steady state conditions, for example when exercise has just begun, tlie C O 2 output lags behind oxygen consumption, oxygen consumption is the more reliable indicator o f energy production. The heart rate monitor was used because the role of the circulatory system is to provide the body tissues with metabolic substrate and oxygen, and to remove via the lungs the carbon dioxide generated by energy production. The cardiovascular system is also responsible for tlie dissipation of excess heat
generated by the performance of work. The cardiac output is matched to the level o f energy expendimre by means of hormonal and central nervous $ystem control. Normal subjects during submaximai exercise show a imear relationship between VO, and heart output and heart rate. Tliis is the basis upon which heart rate and workrate have b ^ n used as uidirect indicators o f oxygen uptake, see [Lcff, 1986]. Tlie correlation between heart rate and oxygen uptake, however, varies widely with thet (legree of fitness of the subjects involved. The use of heart rate m this experiment is as a within!subject measure rather than a between subject measure because of this limitation. The final parameter that was recorded during the experiment was the number of laps of the marked track completed by the subjects in the three minute exercise period. It was hoped that this would give some measure of ability to maintain walking pace under the different stabilisation conditions. Each subject was required to walk around a triangular track, represented m Figure 4, for about two minutes.
Whilst they were doing so they were wearing tlie following equipment:
. i) A weighted waistcoat to carry an Oxylog and a Squirrel data logger.
ii) The Oxylog mask, worn over the face, enabled the subject to breathe ambient air through a vent in the mask and exhale through a non return valve into a flexible hose. This delivered expired air to an oxygen analyzer simated in the weighted waistcoat. All data from the analyzer was down loaded to a data logger.
iii) A heart rate monitor band worn around the chest next to the skin.
A Ï T FWD
Figure 4. Triangular Track.
The prepared subjects were instructed to walk the marked track at a brisk pace whilst the experimenter counted the number of laps and timed the three minute exercise period, indicating to the subject when to stop. The experimenter also used the an electronic indicator tag the start and end of the test and to flag any Mils that occurred during the task.
The motion sickness questionnaires consisted of an "Experiences Today" questionnaire and a motion sickness history questionnaire. The experiences today questionnaire was based on the Subjective Questionnaire used to assess symptoms of motion sickness [de Graaf, Bles, Ooms and Douwes, 1992] and used by the Royal Netherlands Navy. The questionnaire was completed twice by all subjects, on each day (calm and rough) that they completed the performance tests. The first section requested:
personal d ^ l s ; information on quality of sleep the previous night; whether sea-siclotess medication had been taken and i f vomitmg had actually occurred that day. The remainder of the questionnaire asked for information on the degree to which subjects were experiencmg a standard set of symptoms often associated with sea-sickness. The Motion Sickn^s History Questionnaire is one part o f a package of questionnaires developed by (Colwell and Heslegrave, 1993] to collect data on the incidence and. severity of fatigue and. sea sickness symptoms and any associated effects on human perfonnance. (It was completed once only prior to conunencement o f the trial. The first section of the questionnane asked for various personal details, information on past naval experience and use of medication agamst sea-sickness. The main section of the questionnaire asked for information concerning personal experience wiüi sea sickness and more generally, experience of other activities and related forms of motion sickness. The final section of the questionnaue considered sea sickness in more detail and requested subjective opinions on how it affected perfonnance, and the severity of a variety of symptoms. Sea sickness medication was left entirely to tlie discretion of each subject. Each subject was asked to disclose what medication they were cunently taking.
4 Discussion
Stabilisation LFE/roll MUs
Task E and P Stabilisation
Roll angle LFE
LFE/roll MUs Task E and P
ROLL NOTR] ECORDED
LFE 3.4 0.69 0.201 9 NONE 3.7 0.82 0.222 9 NONE 4.2 0.86 0.205 13 ROLL 2.3 0.65 0.284 11.4 LFE 3.8 0.77 0.204 15.1 LFE 3.1 0.64 0.204 20 NONE 5.3 0.96 0.181 20 ROLL 3.2 0.96 0.218 5.5 ROLL 4.6 0.98 0.214 17.4-LFE 5.0 1.04 0.208 34 NONE 3.9 0.84 0.215 21 NONE 4.8 LOT 0.210 24 ROLL 2.4 0.52 0.220 12.3 LFE 2.6 0.53 0.199 12.9 LFE 2.3 0.36 0.158 8.7 NONE 4.2 0.85 0.202 20 ROLL 3.9 0.86 0.222 37.5
Despite considerable effort being devoted to tuning the controller, it was difficult to maintain the rms f i n motion to withm 10 percent for all runs. For example, ip one run the rms f i n motion for the two stabilisation modes was withm 10 percent; in another the difference became 60 percent. Because of the linearity of the controller, it was possible to scale the rms motion relative to a conunon rms fin motion. Table 1 ihows the rms motions and the number of Mils from the two modes of stabilisation scaled relative tp a naean rms fin motion usmg the following formula
and similarly for LFE and, with a little less certainty. Mils.
There appears to be no clear evidence for which mode of stabilisation is better. The rms motions (both roll and LFE) are very consistent across both modes of stabilisation. There are less Mils when stabilising the ship for roll rather than LFE although, because o f the small sample size, the difference is not statistically significant.
12 T
Figure 5: Maximum lateral displacement.
4.1 Postural stability task
For the postural stability experiments. Figures 5 and 6 show tlie range of displacement at each of the markers in the lateral (Y) and vertical (Z) axes respectively. One way analysis of variance (ANOVA) on the results of the posmral stability experiments indicated that the maximum displacement (in both axes) at all markers was significantly lower in the calm condition than in all three rough conditions. The only significant (P < 0.05) difference between tlie three rough conditions was in the vertical (Z)
axis at the sternum, although there was an mdication (P < 0.1) that there were differences In the lateral axis at the left shoulder, right shoulder, sternum and right knee.
A maxunum lateral displacement of nearly 12 cm was observed at the shoulders with tlie body generally becoming more stable towards the feet. Even under calm conditions there was up to 2 cm of displacement,.{lndicating that there is always some inherent body movement present. There were no significant differences in the range of lateral displacement under the various modes of stabilisation, although therè Avas an indication (P < 0.1) that lateral displacement m the upper body was lower under roll stabilisation than no stabilisation.
In view of the values of LFE experienced in the hangar under each condition tliis finding is not surprising. Lateral body movements are unlikely to be different i f the actual lateral accelerations acting on the subject are similar.
Uarker
Figure 6: Maximum vertical displacement.
Figure 6 shows that the range of vertical displacement (up to 3 cm) was smaller than that for lateral displacement and unlike lateral displacement tended to be lowest at the shoulders. This suggests that the heave movements of the ship were compensated for by a dipping movement at the knees. Generally, body movements were greatest at the shoulder and torso and reduced gradually towards the feet. This is not surprising as in effect tlie body was secured to the deck via the feet and body movement would be expected to be lowest at this point. Movements would naturally be expected to be higher at the extremities and at points distant from the feet.
The mean body angle relative to the deck range (measured from one extreme to the other) for all subjects is presented in Figure 7.
(P < 0.05) lower under calm conditions than rough conditions. There was no significant differences when only rough conditions were considered.
Figure 7: Mean body angle
Table 2 shows the significant differences (P < 0.05) revealed by paired T-tests between all conditions. The mean angle range varied from 2 degrees (the vertical angle under calm conditions) to 6 degrees (the horizontal angle under rough conditions with no stabilisation). Examination of the cycle of the two angles over the digitisation period revealed a high level of synchronicity. In addition, the maximum mean difference between these two angles was less than 2 degrees, which suggested that personnel, as instructed, maintained their initial posmre to a high degree. Pivotal movements at the waist were therefore negligible in terms of angular movement.
Horizontal Vertical
Calm V LFE Calm < LFE Calm < LFE Calm V roll Calm < roll Calm < rolf Calm V None Calm < None Calm < None
LFE V roll roll < LFE (*) N.S. roll V None roll < None (*) roll < None (*) (*) - Some indication of a difference i.e. P < 0.1
Table 2. Mean angle range - significant differences revealed by T-Tests
More detailed analysis of the angular data with the simultaneous ship motion could provide interesting information on the relationships between the body angles and for example the roll angle of the ship.
This would mdicate whether individuals acmally move with the ship (i.e. motion cycles are synchronised), or individuals anticipate the motions (i.e. body movements are slighUy ahead), or they respond to the ship motion (i.e. body motions lag slightly beliind). This information on the various strategies employed by mdividuals to cope with ship motion could be used for example m training mdividuals to act-in a different way so as to mmunise the number of Mils experienced.
Analysis of the; videotape revealed a total of 27 body lateral (as opposed to body longitudinal or fore/aft) MHil which occurred m all modes of stabilisation durmg the rough water trial (this is to be compared with the stumble/fall indicator showmg a total of 22 MHs): 5 whilst tiie ship was under roll stabilisation; 10 under no stabilisation and 12 under LFE stabilisation. No MOs were observed during the calm water trial. Kruskal-Wallis ANOVA revealed that there was a significant (P < 0.01) difference between the four conditions (i.e. mcluding calm). The Wilcoxon Matched-Pairs Signed-Ranks Test was used to test for specific differences between the four separate conditions. This revealed that tlie number of Mils was significantly lower (P < 0.05) m the calm water condition than any of tlie three rough conditions. There were no significant differences between the three rough water conditions, although there was some indication (P < 0.1) that tiiere were fewer Mils in the roll mode of stabilisation than when the ship was stabilised for LFE. There was no order effect i.e. the number of Mils did not differ significantly over the course of the three conditions (irrespective of the sequence of diese conditions). There was no difference in the number of Mils tliat each subject experienced i.e. it did not appear that particular individuals had a higher susceptibility to suffer Mils. There was an identifiable trend with bodily movements greatest whilst the ship was not stabilised, at a minimum under roll stabilisation, with stabilisaUon for LFE providing intermediate values. As LFE stabilisation of the ship did not produce the expected reduction in lateral accelerations in the hangar, the absence of any significant difference in lateral body movements is not unexpected. Body movement at the various markers also followed a general trend with body movements tending to be greatest at the shoulders and stemum with a subsequent decrease towards the feet.
The number of observed Mils was disappointingly low. Only 27 lateral Mils were observed during a total subject exposure to rough water conditions of 1 hour and 48 minutes; no longitudinal Mils were observed. The heavy swell Üiat accompanied this sea stole 3 guaranteed-that the ship rolled heavily at limes but ils cyclical nature ensured that subjects were usually able to anticipate ils pattem and therefore avoid Mils.
4.2 Exercise task
Energy Expenditure has been calculated from the oxygen uptake measured by the Oxylog/squirrel dato logger equipment. The average of the results of the minute volume is shown in Figure 8.
The figure shows a rising trend in each of the test conditions as well as the baseline measurement minute oxygen uptake showed similar characteristics. It can also be seen that during the test conditions the initial Vg is higher than at rest. This is lo be expected as the subjects were experiencing and reacting to significant ship movements during the period before actual participation in the exercise
part o f the experiment.
Figure 8: Average minute volumes of oxygen for eacli minute of exercise.
Figure 9 sliows tlie average of the heart rates across all conditions.
The variable namre of the traces can be correlated to the track walking task, the track was laid out as a right angled triangle shown in Figure 4. The subjects all started at the acute angle and walked clockwise, on each lap the subjects slowed momentarily to negotiate this acute angle, the heart rate monitor recorded the average rate per five seconds. When the five second heart rate averaging period and the lap coincided the heart rate showed a dip at this point.
Avaraga haart ralas va StablllaaUon
BUbllliarcondKlan
Figure 9: Average heart rate at the end of task E.
The walking speed measure was included to see if it was sensitive to the different modes of ship stabilisation. The average of all results for all subjects are shown in Figure 10. A paired T-test
(dependent samples) was used to test for significance.
There were significant differences (P < 0.05) between the calm baselme and the two actively stabilised conditions, but not between the calm and unstabilised rough conditions (P > 0.1).
Lap numbw » . 4 ts.o 12.S t3.0 1J.4 12J 12.0
/
/
/
z crj.m l!0Figure 10: Walking .speed during task E
This may be due to the differences between die unstabilised condition, where aldiough the rms ship motions were higher, it was predictable to tlie subject, whereas tlie stabilised conditions were less predictable to tlie subject, who then had to compensate for the changes in motions by more carefiil steps and a slower overall walking pace. Alteniatively, die rough motions could have caused the subjects to walk faster (i.e they just want to get die task over wiüi); large motions could also encourage the subjects to cut o f f die comers of tiie triangular track. In tiie calm water case tiie subjects had no motion to contend witii and tiius tiiey took great care in walking along tiie track and taking each comer completely. Furtiier analysis of tiie video should give more information.
4.3 Tapping task
Figure 11 summarises tiie raw data obtained from the tapping task.
to 4 . ' C«Im Non» Roll I f E
Condition
The results o f the ANOVA carried out on this data are presented at Table 3. Subjects demonstrated a significant reduction in accuracy (P < 0.01) under the rough water condition when compared to the calm water condition.
EFFECT
No. of Targèts •hit'
Time of Completion
ROUGH WATER ONLY
M^de of Stabilisation 0.7953 0.9452
Order ( I , 2 or 3) 0.5345 0.081
ALL CONDITIONS
Sea state (CALM or ROUGH) 0.008 * 0.001 *
Order (1, 2, 3, or 4) 0.006 * 0.001 *
*Significant at 1 % level
Table 3. Tapping task - results of analysis of variance (P values).
However, this was accompanied by a significant (P < O.OI) reduction in the time which it took to complete the task. Due to the practical limitations of the trial it was not possible to completely balance the order of the conditions, all subjects completing the calm water trial prior to any o f the rough water conditions. Consequently, these differences may simply be a consequence of the learning effect that is a characteristic of many tasks of this type. There was no significant difference between the modes of stabilisation eidier for accuracy or for the time taken to complete the task. There was however, an indication (P < 0.1) Üiat an order effect for time of completion of the task existed (i.e. subjects tended to complete the task faster with increased exposure), the balanced order of the conditions ensured that this did not distort the results. The possibility exists that this particular task was not sensitive enough to the changes ih the ship motions brought about by the different modes of stabilisation, and that the use of a more sensitive task may have highlighted subtle changes in performance.
4.4 Questionnaire
The Wilcoxon matched-pairs signed-ranks test was used to analyse the results o f the "Experiences Today" questionnaire specifically to assess die differences between subject responses on the calm and rough trial days. Symptoms that were noiiceably more severe on the rough trial day than the calm water day are listed in Table 4.
A large number of symptoms üiat are often associated widi sea sickness were reported to be more severe under the rough water conditions than the calm water conditions, suggesting that many of the subjects involved were quite badly affected by sea sickness during the rough water trial. Unfortunately many of these symptoms are not specific solely to sea sickness and it is possible that external and uncontrolled factors caused some of die reported deteriorations. In particular the requirement for
rough conditions and the progranune of the ship ensured that the rough water human factors trials were carried out during the middle of the night. This contrasts with the calm water trials which were carried out durmg the early evenmg. A duect comparison of the symptoms which make up the 'fatigue' factor is therefore mvalid due to the fact that many of the subjects were working during then normal sleep period in the rough water trials. However the 'nausea' factor (consistmg o f increased salivation, stomach awareness and sweating) can be compared. Two of these three symptoms were significantly more severe under the rough water conditions mdicatmg that the subjects did feel more nauseous tlian during the calm water trial.
SYMPTOM P V A L U E Dizziness 0.068 * Yawning 0.042 ** Stomach Awareness 0.075 * Fatigue 0.012 ** Tension / Anxiety 0.075 * Sweating 0.068 * Headache 0.022 ** Drowsiness O.OIl **
Quantity of Sleep (previous night) 0.028 ** *(P < 0.1) - An indication that symptoms were more severe on rough trial day. **(P < 0.05) - Significandy more severe symptoms on rough trial day.
Table 4. Experiences Today Questionnaire - Results of Wilcoxon test (P values)
The replacement of the symptom list wiüi a simpler and shorter meüiod of assessing subjective feelings of sea sickness at any particular time, has been previously considered widi die development of die 'Misery scale' shown in [de Graaf, Bles, Ooms, Douwes, 1992]. The data provided from die "Experiences Today" questionnaire provided some preliminary daU that was used to assess the validity of Üiis scale as a replacement for die symptom list. This was achieved by'summing the scores reported for die symptomatology list and correlating this value wiüi die value given by each individual for die Misery scale. This revealed a Spearman correlation coefficient of 0.66 widiin die calm condition (significant at P < O.OI level) and a coefficient of 0.73 widiin die rough condition (P < 0.01). Grouping die data produced a Spearman coefficient of 0.68 which is significant at die P < 0.01 level. These results indicate that even widi a small sample size of 18 individuals, results from die Misery scale correlate well with Üiose from die symptomatology list, indicating diat it could be validly employed as an easier alternative method of assessing sea-sickness severity.
Four subjects reported taking sea sickness medication, all of whom took it on the day of the calm water trial (36 hours after sailing), and two who took it on the day of die rough water trial (4 or 5
days after sailing). None of die subjects reported vomitbig on eidier of the trial days.
The main finduigs highlighted by the analysis of the data ft-om the motion sickness history questionnaire were that fifteen of the eighteen subjects had experienced sea sickness at some time. Of these, only four subjects indicated that sea sickness caused a decrement in theh ability to carry out mental tasks. Jobjerformance, physical tasks and attentive abilities were all reported to be unaffected by sea sickness.)It should be noted that there is not evidence that the subjects indicating a performance
• f
decrement from seasickness were acmally poorer at the tasks smdied in this trial.
Fifteen of die eighteen subjects reportöi that they had suffered from sea sickness at some' time although none experienced it during the LFE rough water trials. Prior to the frial there was a concern diat sea sickness of die subjects might have become a problem and this necessitated die optional use of sea sickness medication for all subjects. In the event, only two subjects took sea sickness medication prior to the rough water trial, and neidier of diese, or diose subjects who did not take medication complained of feeling sea sick (aldiough results from die "Experiences Today" questionnaire did indicate diat symptoms of sea sickness were more severe dian during die calm water trial). The absence of specific complaints of sea sickness during this sea state 3, corroborates with information given in the personal history form that a sea state 3 was the minimum required to produce sea sickness in any subject.
4.5 M i l model
Figure 12 shows the type of rigid body model by (Graham, 1990]. It considered die forces acting on a person in a frame of reference fixed to the ship.
[Graham, Baitis and Meyers, 1992] extended die work of Üie previous paper to mclude the effects of non zero vertical acceleration and steady and non steady wind. The reference also estimated the moment of inertia of die body by modelling die person as an ellipsoidal cyluidcr. This introduced an additional term which mcludes the roll acceleration to give:
a tip or M n to pOrt will occur i f
, 4/4-5,-9*453 > (6)
'{•
and a tip or M i l to starboard will occur i f
-^h^*S,*g^-j^S, > I g (7)
These mediods for estimating die incidence of Mils are derived from a model of the forces acting on a standing human. They provide a means to determine when motions will interfere with manual tasks such as helicopter deck handling and general maintenance.
So, according to die inequalities (6) and (7) an M i l will occur whenever
5,4h<l]
=(9*^3)4
(8)rearranging gives an equation for the tipping coefficient , which varies with time.
Figure 13 shows an example of die tipping coefficient varying widi time. The graphs show boüi die posmral .stability and exercise task. Clearly, in diis case more Mils occur during walking than standing still.
M i l number Ctip at M i l
-I
Ctip at local maximum Time of M i l
Exercise 1 0.299 0.299 397.7 2 0.285 0.305 416.1 3 -0.031 -0.031 432.1 4 0.301 0.307 485.8 5 0.289 0.302 560.2 Posture 1 0.391 0.415 751.4 2 0.323 0.380 773.2 Table 5. Sample of M i l s
The point in time where an M i l occurs was indicated by die event markers, shown in Figure 13 by dotted lines. The event markers must, in general, have recorded die M i l after die actual event. It
therefore seemed appropriate to associate the event with a recent maximum value. A sample of the data is shown in Table 5.
Figure 13: Example of Clip time histories.
Most Mils occur at or near a peak value for die tipping coefficient. The third M i l recorded in the exercise routine occurs at a low value for Ctip. Here the M i l can not be explained by die tipping forces.
It is posmlated that Mils can be classified into 8 categories. A M i l at/near a smooth peak.
B = M n at/near zero accelerations.
C M i l at unexpected change in die motion profile. AC M i l at/near a peak with profile not smooth. D M i l not explained by considering tipping forces. E M i l too near start and stop of experiments. F M i l occurring too near previous M i l . X Others not covered by the above.
As far as validating die M i l model the types of most use are A and AC. Table 6 gives a summary of die types of Mils occurring for bodi exercise and postural stability for all subjects in all modes of stabilisation.
A large proportion of die total Mils (about 70 percent) are types A and AC. The other 30 percent of the Mils could be analysed in more detail using die video records. Collating all the posmral Mils and
extractiog the maximum value of tipping coefficieat upto 4 seconds before the event marker gives an cmpkical value for the tipping coefficient of 0.294 from a total o f 22 recorded Mils. Carrymg out similar analysis for die exercise task gives a mean tippmg coefficient (at v/hich an M i l occurred) of 0.156. It must be noted that this task is a walking task while the MH model was developed for a two footed static posture.
. t y p e Postural Exercise
. t y p e
Number % of total Number % of total
A 15 68 163 62.5 AC 1 4.5 22 8.5 B 5 23 33 12.6 C 0 0 9 3.4 D 1 4.5 20 • 7.7 E 0 0 3 1.1 F 0 0 11 4.2 X 0 0 0 0 TOTAL 22 (0.20 miis/min) 100 261 (1.71 miis/min) 100 Table 6. Summary of M i l s
Figure 14 shows an example of a peak count of the tipping coefficient fime history. According to the theory die number of peaks exceeding a threshold is directly related to the number of Mils. From Figure 14 it can be seen that there are a significantly lower number of large peaks for roll stabilised than die oüier two modes of stabilisation. Figure 14 shows that, in this particular example, roll stabilisation was better than LFE stabilisation and no stabilisation.
T 1 r
N p m k E u h i c h ( N c c i d C t i p t p t a k )
Figure IS are histograms showing a sample count o f the peak tipping coefficients which cause an M i l durmg the exercise task and a sample count of the peaks o f tiie tipping coefficient.
In total there were 244 M i l and 1938 Ctip peaks. The ratio of the ordmates of tiiese two histograms give die probability of an M i l occurring at a given tipping coefticient (for tiiis task and motion profile). For example, tiiere were 25 Ctip peaks at tiie 0.15 level tiiat caused an M i l ; tiiere were acmally 147 Ctjp peaks at tiie 0.15 level m tiie time history. So, tiie probability of an M i l occurring, given that thd tipping coefficient has achieved a level of 0.15 is 25/147 = 0.17.
This Is represented by
P(MI1 occurring at a given Ctip peak)= Number of M i l at a given Ctip peak (9) Number of peaks at that level
3 » r .LlLl . 8 M t «3 a 16 t | } ( 28 »n • la a JS a 4a C t l p c a u s ing an til I 5 « e r _ i l T h T - r m i i i i i i i i i i e ea en e te a is a 2e »n e ja a i s a.*» C l i p p e a k s
Figure 15: Histograms of Ctip peaks.
probability of an M i l occurring for that level. In fact. Figure 16 shows that there is a finite probability of an M i l occurring at any levels of Ctip; which is what could be expected. The model developed by [Gra]iam,1990] was an attempt to simplify a complex biodynamic problem. This probabilistic approach is an attempt to model some of the uncertainty of human responses.
An empirical curve could be fitted to the data shown m Figure 16; which could be dien used m furdier M i l calculations. However, by making assumptions concemmg the statistical distribution of the measuredivariables (i.e, the p.d.Q a more analytic solution can be sought.
KEY 0 Dala Raijlaigh H o r m l t . M • I t C l i p
Figure 16: Probability density functions.
Figure 17 are die p.d.fs of a normal and Rayleigh distribution compared widi the experimental data. It can be seen that die probability of a Ctip peak causing an M i l can be approximated by a Normal distribution; whilst the probability of a Ctip peak can be approximated by a Rayleigh distribution. Tlie justification for diis is based upon die recognition that the peaks of a ship motion profile in an irregular wave are Rayleigh distributed. Because of linearity it could be assumed Üiat the Ctip time
history, which consists o f components of the ship motion profile, is also Rayleigh distributed. The assumption that the distribution of MUs at each Ctip peak is normal is based purely on uispection; an alternative distribution may be more appropriate but has not been considered at this time.
t l » I I S I I I I I S I H • » I M I M * M I «3 I H
Clip
Figure 17: Probability of M i l at any Ctip.
So,
P(M1I at a given Ctip peak) = P(Ctip causing an M i l l x 11. (10) P(Ctip peak)
which becomes.
i f " ^ " - - E
/2n
P ( M I I a t a g i v e n C t i p ) = " ' ^ ^ ( ^ ]
Unfortunately, this gives invalid values for the probability curve for high Ctip. This could be due to an incorrect assumption that the probability of a Ctip causing an M i l has a normal distribution. Alternatively it could be due to the fact diat diere were insufficient Ctip peaks at'diese high levels to achieve statistical stability.
An empirical correction can be introduced at this stage; which could be validated with further experiments.
A multiplication factor could be introduced to replace the final term in Equation 11 which forces the probability curve to become 1.0 at a nominal value. The nominal value for diis smdy was chosen to
be twice the mean tipping coefficient .
So, the probability o f an M i l occurring at a given Ctip can be represented by P ( M I I a t a g i v e n C t i p ) where
c
i/ctlpv c t i E « ^ { V ) 1.0 — C for Ctlp £ 2 ^ ( TV 1 3. - l i e n " J for c t i p > 2 4 (12)This empirical probability curve is shown in Figure 18.
Tlie result is encouraging, the empirical curve follows the experimental data satisfactorily. This probabilistic approach could be used to 'improve' the model devised by [Graham, 1990] to determine the total number of Mils as shown.
7 n I u
i. iMh
I¬
I M % * — i •s • « 1 1 1 1 1 1 f i t ?-Figure 18. Empirical curve for probability of M i l occurring at any Ctip.
Using die notation adopted by [Graham, 1990].
rp 0 . 5 . 1 / C t i p g \ '
^tSLi C t l p - 0 . 0
P ( M I I a t c t i p ) (13)
The above equation means diat, for each Ctip peak diere is a finite possibility of an M i l occurring; by summing over the full range of values for Ctip a prediction of the total number of MUs can be made.
5 Conclusions
Because o f the variability of the sea state, it was difficult to maintam the rms f i n motion of both LFE and roll stabilisation to within ten percent. This caused some problems in making direct comparisons between modes o f stabilisation.
However, from^^e motion perspective, there appears to be no evidence to suggest that LFE stabilisation is superior to roll stabilisation. There is slight evidence to suggest that roll stabilisation is better; this! result is consistent throughout all the 'performance' measures. It is unclear why this result was obtained, but it could be due to mcorrecdy mning the fins for LFE. Reference 10 gives a procedure for mhing the ships' fin controllers to stabilised for LFE.
What has yet to be established is whedier humans are able to cope with the characteristics of motion associated roll stabilisation better dian those associated with LFE stabilisation. That is by minimising the LFE motion perhaps the first derivative of LFE ( called jerkiness or jerk) is increased to an extent diat more Mils are observed.
The examples shown in this reference (Figure 5) were derived from a standard roll stabilisation tuning procedure adopted for LFE. The reference pointed out that due to the high frequency content in the LFE signal, the controller settings should have a lower response to this high frequency compared to the reference settings (roll stabilisation). This was to avoid fin samration due to the excessive high frequency demand. Perhaps, it is not pertinent to use die same mning procedure for LFE stabilisation as diat used for roll stabilisation.
Clearly, no further ship trials are practical in die foreseeable fiimre, so numerical smdies could look at assessing and refining the mning procedure developed earlier.
The mode of ship stabilisation employed during the rough water trial did not significantly affect the posmral stability of the subject. There was however an identifiable trend with roll stabilisation appearing to produce the lowest body movements, no stabilisation producing the greatest movements widi LFE stabilisation producing intermediate values.
Time to complete die tapping task and the accuracy with which it was completed were not significantly affected by the mode of ship stabilisation employed during the rough water trial. The combined results show that the tests applied are all sensitive enough to differentiate between calm and the experimental conditions. However the energy consumption test did not differentiate between the experimental conditions as expected, probably due to die subjects not achieving steady state exercise levels in the 3 minute period allotted for this task. The solution to this is in ftimre is to ensure a longer exercise period, even at the expense of the number of subjects that can undertake this experiment.
The ship trial has shown that it is possible to gadier physiological data from subjects in a dilïicult environment, and that it is possible to perform complex human factors experiments that involve a number of differing tasks and multiple subjects in an efficient manner.
These conclusions apply to motion simulation systems as well as potential fumre field trials. It would be appropriate to extend diis type of measurement to measure energy uptake and cognitive
performance in extended workstation based simulation tasks m motion simulator based trials. Tbe results from this type of work could be used for enhancmg the habitability and ship performance models that are under development within die UK.
A large number of the symptoms reported m the "Experiences Today" questionnaire were probably related to fatigue; Due to the constrauits of other trials is was only possible to carry out the rough weather trial during the night. Some of the symptoms were related to nausea and in some cases these proved significant. The results of the comparisons between the symptom list and The Netherlands' 'Misery' scale shows a high correlation even at this small sample size. This corroborates die high correlation found from smdies undertaken m The Netherlands.
One of the objectives of the trials was to increase the human performance database to validate/improve the mathematical model proposed by [Graliam,1990]. Empirical tipping coefficients have been derived for the standing and walking tasks. Unformnately, the low number of Mils observed during the standing task means that the empirical tipping coefficient has been determined widi little statistical reliability. However, die analysis has shown tiiat the tipping coefficients used for fumre calculation involving the Graham model should be
Walking task tipping coefficient = 0.156 Body lateral tipping coefficient = 0.294
The authors* have proposed a new approach to predicting Mils. It is conjecmred that the 'step* function ( step function in the sense that an M i l will occur i f and only i f die forces exceed a given level) proposed by [Graham, 1990] can be improved by adopting a probabilistic approach. This means that there is a finite probability of an M i l occurring at aU levels of force. The probability of an M i l at low forces is low and increases to 1.0 at high levels. The rate of increase of probability is dependent upon the distribution of tipping coefficients at which Mils were recorded. This approach lends itself to determination in the firequency domain by integrating the number of M i l over a range of fipping coefficients.
6 Acknowledgements
The authors would like to thank the commanding officer, the officers and crew of-HMS IRON DUKE for the oppormnity to carry out these trials and their participation in them.
The authors acknowledge Mr P Wilson and Dr A Tang from the Department of Ship Science, University of Southampton for the efforts in designing and building the LFE controller and for their participation in earlier LFE stabilisation smdies.
This project was supported by the Procurement Executive, Ministry of Defence.
® British Crown Copyright 1994 /MOD. Published widi die permission of die Controller of Her Britannic Majesty's Stationery Office.
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8 Glossary of terms
Alphalog A portable heart rate monitor and logger that is attached to the subject by a two electrode chest band. The unit records heart rate at 5 second intervals.
ANOVA . One way analysis of variance. .
APRE Army Personnel Research Establishment. .
ATP Adenosme triphosphate. This is die obligatory hitermediary metabolite used by die contractile mechanisms in the muscles. Tliis is formed from adenosine diphosphate by the catalysis of energy substrates e.g. fats and carbohydrates.
BTPS fThe volume of gas measured at body temperamre and pressures (litres)
GLFE 1 - Generalised lateral force estimator accountuig for non zero vertical acceleration I N M lostimte of Naval Medicine
LFE Lateral force estimator M i l Motion induced interruptions
Oxylog A portable oxygen uptake and ventilation rate data logger. The equipment is carried by the subject, who breaths Üirough a closely fitting oro-nasal mask. Flow rate through die mask is measured, and the oxygen uptake measured by a differential mediod between exhaled and ambient air.
PCO2 Partial pressure of Carbon Dioxide in the arterial blood (mm Hg) RLS Rudder LFE stabilisation
RQ Respiratory Quotient. This is die ratio of Oxygen consumption to carbon dioxide production. It is 1 for pure carbohydrate metabolism, and 0.7 for pure fat metabolism.
RRS Rudder roil stabilisation
STPD Volume of gas corrected to Standard Temperamre and Pressure Vy^ Alveolar ventilation rate in steady state conditions (ml /min) V E Minute ventilation volume (l/min)
