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B�:	Biomechanics of Slips and Falls in the Elderly and Young using Upper and Lower Body Center of Mass Dynamics

Aditya Jayadasa and James L. Smithb 
aDesign, Housing & Merchandising Dept., Oklahoma State Univ., Stillwater, OK, USA
bIndustrial Engineering Dept., Texas Tech Univ., Lubbock, TX, USA
*e-mail:  HYPERLINK "mailto:aditya.jayadas@okstate.edu" aditya.jayadas@okstate.edu 

ABSTRACT

Background: Slip and fall accidents continue to be a growing problem as they relate to elderly individuals. Researchers have studied different gait parameters pertaining to the biomechanics of slips and falls. However, a comprehensive understanding of mechanisms including strategies used for recovery during a slippery perturbation is still lacking. The traditional approach has been to explore the dynamics of the whole-body-center-of-mass (WBCOM) as it relates to the base-of-support (BOS) during a slippery perturbation. 

Purpose: The purpose of the current study was to explore a novel approach for studying the biomechanics of slips and falls using the dynamics of the upper-body-center-of-mass (UBCOM) and the lower-body-center-of-mass (LBCOM).

Methods: Twenty-eight individuals (14 young and 14 elderly) with an equal number of males and females participated in the study. Individuals were required to walk along a circular track and they were exposed to an �unknown� slippery floor condition. The gait trials were monitored using an 8-camera motion capture system.  

Results: Eight out of 14 elderly individuals fell whereas only three out of 14 younger individuals fell when encountering a slippery perturbation. The results indicated that elderly individuals who fell had a greater difference in velocity between the LBCOM and UBCOM when compared to the younger fallers.  In addition, the younger non-fallers had a greater difference in velocities between the LBCOM and the UBCOM when compared to the elderly individuals and were still able to recover. This suggests that the elderly individuals were more likely to fall from a slippery perturbation as they were not able to use a successful �catch up� strategy and move the UBCOM fast enough with respect to the LBCOM to prevent a slip-induced fall.  

Conclusion: Findings from this study clearly show a need for a better understanding of the dynamics of the upper and lower body under slippery conditions. 

Keywords: Whole, upper and lower body center-of-mass, slip-induced fall







Introduction

	During gait, the human body is in an inherent state of instability.  The instability is apparent in that for 80% of the gait cycle, the body is in the single support phase, implying that only one foot is in contact with the ground (Winter, 1991).  When the body moves from single support to double support, during the heel contact phase, there is a possibility of a slip-induced fall as the weight acceptance task is being transferred from one foot to another (Lockhart, 2000).  Though the potential for a loss of balance from a slip-induced fall has been addressed in the past, the state of dynamic instability is only beginning to be understood.
The gait cycle begins with the initiation of gait through the forward movement of the body, which is an unstable event since the whole body center of mass (WBCOM) is made to fall forward and outside the stance foot (Winter, 1991).  The only stabilizing period during the gait cycle is during the double support phase, when both feet are on the ground.  However, a potential threat to balance does exist when the swing limb initiates contact with the ground in preparation for the double support phase.  As the foot makes contact with the ground to initiate the role of weight acceptance, a high heel contact velocity could lead to a slip-induced fall (Winter, 1991).  This higher heel contact velocity has been reported to be more prominent in the elderly individuals when compared to younger individuals.  Lockhart, Woldstad & Smith (2003) reported that elderly individuals had a higher heel contact velocity in their effort to bring their foot down faster in order to spend more time in the double support phase, thus making them more susceptible to a slip-induced fall.  When the heel begins to slide after making contact with a slippery surface, a slip-induced fall occurs when the WBCOM of an individual is thrown out of balance with respect to the BOS (You, Chou, Lin & Su, 2001).  In other words, a smaller separation and a faster velocity of the WBCOM with respect to the BOS were required to regain balance.  This traditional approach of comparing the position and velocity of the WBCOM to the BOS, however fails to address the specific question: Is the slower reactive response of the upper body, which contains 67.8% of the total mass of the body (as reported in Winter, 2005), the primary contributor to a slip-induced fall?  In other words, could the LBCOM as it relates to the UBCOM dynamics provide a better understanding of slips and falls in the elderly?
The purpose of this study was to understand the dynamics of the LBCOM and the UBCOM during a slippery perturbation.  The specific questions that were posed were: (1) Is the LBCOM-UBCOM approach a better approach in distinguishing fallers and non-fallers when compared to the WBCOM-BOS approach? (2) Is there a threshold for the velocity values between the LBCOM and the UBCOM that results in a recovery or fall? (3) Are their differences in age between the velocity values for the LBCOM and the UBCOM?  It was hypothesized that there would be a threshold difference in velocity value between the LBCOM and the UBCOM beyond which individuals would fall.  It was also hypothesized that elderly individuals who fell would have larger differences in velocity values between the LBCOM and the UBCOM when compared to younger individuals who fell.  On the other hand, it was also hypothesized that younger individuals who recovered would have a larger difference in velocity values between the LBCOM and the UBCOM when compared to older individuals who recovered.
Methods

Experiment location and approval

The research study was conducted at the Ergonomics Laboratory in the Industrial Engineering Department at Texas Tech University (TTU).  All procedures for this study were conducted upon approval from the Texas Tech University Institutional Review Board for the protection of human subjects.
2.2 Subjects

	Twenty-eight individuals were recruited for the study.  Specifically, 14 young adult (7 male and 7 female) and 14 elderly (7 male and 7 female) individuals   from the university and elderly community in Lubbock, Texas volunteered to participate in the study.  The 14 elderly subjects ranged as follows in age (65-80 yr), height (1.56-1.93 m) and mass (56.4-113.2 kg).  The 14 younger subjects ranged as follows in age (20-33 yr), height (1.63-1.88 m) and mass (44.7-101.6 kg).  All the individuals were in good health and passed the screening procedures required for participation.  Individuals were screened for heart problems, blood pressure, shortness of breath, dizziness, fatigue, discomfort in hip, knee and/or ankle joints, difficulty in walking, difficulty with cognition and history of prior falls.  Further, individuals were required to do a practice gait trial while wearing a whole body fall protection harness.  If individuals indicated difficulty in walking, they were not included in the study.  It must be pointed out that as in a previous study (Lockhart, Woldstad & Smith (2003), the older individuals who volunteered for the study were a healthy active group and most likely not typical of an elderly population such as we might expect to find in a nursing home population.  No monetary benefits were provided to the subjects for their participation in the study.  
2.3 Experimental set-up and protocol

	Gait trials were performed on a circular track equipped with a fall arrest rig system.  Subjects walked at their preferred walking speed.  Motion data were captured using an 8-camera motion capture system from Motion Analysis Corporation (Santa Rosa, California, USA).  The sampling rate used for the motion capture of the 3-D (dimensional) position data using reflective markers was 120 Hz.  Marker coordinate data were smoothed using a 4th order zero lag Butterworth filter with a cut off frequency of 6hz.  Nineteen reflective markers were placed on each individual at various palpable locations.  The marker protocol previously used by Lockhart (2000) was modified and used in the study.  Markers were placed bilaterally on the ulnar styloid process, lateral epicondyle (estimating elbow axis), temporal bone (above the ear), acromion process (most lateral part), greater trochanter, lateral femoral condyle, lateral malleolus, head of second metatarsal, heel and on the sacrum.  The heel marker and the markers on the second metatarsal head were placed on the shoe.  A stick figure was created from the 19 markers to provide a visual model by which to better understand the recovery effort during a slippery perturbation.  The stick figure snapshot for a slippery trial for one individual attempting to recover is shown in [Figure 1] below.   
<INSERT FIGURE 1 HERE>
	Individuals were required to walk for several trials during �dry�, �known� and �unknown� slippery conditions.  Only the three �unknown� slippery trials, where individuals were not aware of the slippery surface and slipped, were included in the analysis for the current paper.  Thus a total of 28 �unknown� slippery trials (one trial per subject) were analyzed.  The time window for the analysis included slip initiation after initial contact of the foot on the unknown slippery surface to slip termination.  
2.4 Calculation of the LBCOM and the UBCOM

	 The LBCOM and the UBCOM were calculated from the coordinates of the 19 markers and anthropometric information (Winter, 2005).  The LBCOM segments included left and right thighs, legs, and feet.  The UBCOM segments included the head and neck, trunk, left and right upper arm, forearms and hands.  
The resultant velocities for the LBCOM and UBCOM were then calculated from the 3D positional data using central finite differences.  The maximum differences in velocities for the LBCOM and the UBCOM were calculated for both scenarios, when the LBCOM was trailing and leading the UBCOM. 
2.5 Classification of the outcome of the unknown slippery trials

	The outcomes of the 84 �unknown� slippery perturbations were classified as �recovery� or �fall�.  A trial was classified as a �fall� if the resulting vertical load exceeded 100 N as detected by the fall-arrest-rig (FAR) system which would cause the machine to shut down and support the individual fully using the full-body-harness system attached to the FAR.  If individuals did not exert a vertical force greater than 100 N on the FAR the trial was classified as �recovery�.  Individuals who fell were classified as �fallers�, whereas individuals who recovered were classified as �non-fallers�.
2.6  Statistical Analysis

	Independent t-tests were used to test difference between fallers and non-fallers, younger and elderly fallers, and younger and elderly non-fallers.  Alpha level was a set priori to 0.05.
Results

	Five out of the 14 elderly individuals fell when compared to three out of the 14 younger individuals.  A total of 8 fall trials resulted from the 28 �unknown� slippery trials, and 70 trials resulted in recovery.  Three of the eight falls were in the forward direction, while five were in the backward direction.
	In terms of the maximum difference in velocities between the WBCOM and the heel, it was found that there were no significant differences between fallers and non-fallers when the WBCOM was moving faster than the heel (P=0.47) and when the heel was moving faster than the WBCOM (P=0.24) as seen in [Figure 2] and [Figure 3] respectively. 
<INSERT FIGURE 2 HERE>
<INSERT FIGURE 3 HERE>
	In terms of the maximum difference in velocities between the LBCOM and the UBCOM, it was found that the LBCOM and UBCOM velocities differed between fallers and non-fallers. Forward fallers (when the UBCOM was moving faster than the LBCOM) exhibited a 0.18 m/s greater velocity difference (P = 0.02) than non-fallers [Figure 4].  Backward fallers (when the LBCOM was faster than the UBCOM) exhibited a 0.16 m/s greater velocity difference (P = 0.03) than non-fallers [Figure 5].
<INSERT FIGURE 4 HERE>
<INSERT FIGURE 5 HERE>
 	Next, taking into account age, for the fallers, the older fallers exhibited a 0.28m/s greater velocity difference (P= 0.03) when compared to the younger fallers.  As for the non-fallers, the opposite was true, with the younger non-fallers exhibiting a 0.15m/s greater velocity difference (P = 0.003) when compared to the older non-fallers (Figure 6).  
<INSERT FIGURE 6 HERE>
Discussion

	The results from the study showed that LBCOM-UBCOM approach was able to better distinguish fallers and non-fallers when compared to the traditional approach of using WBCOM-BOS, thus supporting the first hypothesis.  The LBCOM-UBCOM approach can be better explained through sample trials from the study showing differences in velocities between the LBCOM and the UBCOM for a fall and recovery trial as shown in Figure 7.  For the fall, it can be observed that the differences in velocities between the LBCOM and the UBCOM starts as a negative value indicating that the UBCOM was moving faster than the LBCOM, but the value becomes positive shortly after ~t=0.15 seconds and does not return to a negative value.  This suggests that for the positive part of the graph, the LBCOM was moving faster than the UBCOM and the UBCOM could not �catch up� with the LBCOM, thus resulting in a fall.  On the other hand, for the recovery, the differences in velocities between the LBCOM and the UBCOM starts off as a negative value, then becomes positive and later returns to a negative value.  This suggests that the UBCOM was able to �catch up� with the LBCOM, regain balance and avoid a fall.  
<INSERT FIGURE 7 HERE>
	The successful catch up of the UBCOM with the LBCOM could have resulted from a rapid arm movement which is crucial for recovery as suggested my Marigold, Bethune & Patla (2003).  Further, this arm movement could have helped move the trunk forward which accounts for most of the mass of the upper body.  Troy, Donovan & Grabiner (2009) reported that arm responses served to reduce trunk rotational velocity immediately following the slip while repositioning the UBCOM away from the rear support boundary.  The trunk kinematics and the UBCOM velocity could thus be crucial in recovery.  The question that could be raised is what about the WBCOM velocity in relation to the heel.  Does that not explain the same �catch up� strategy?  
	Thus the catch up strategy was further explored to see if the same held true for the heel and WBCOM.  Sample fall and recovery trials for the LBCOM and UBCOM, and the WBCOM and heel are shown in Figure 8 and Figure 9 respectively.  While the recovery trial (refer Figure 8) did show that the WBCOM was always faster than the heel, the fall trial (refer Figure 9) suggests that the WBCOM was faster than the heel but a fall resulted.  This is not in agreement with the �catch up� strategy proposed here where a fall results when the UBCOM was unable to catch up with the LBCOM. 
<INSERT FIGURE 8 HERE>
<INSERT FIGURE 9 HERE>
	Use of the UBCOM as a representation of the trunk kinematics appeared to be a valid argument in that just as a fall resulted when the trunk was closer to rearward boundary of the base-of-support, a fall resulted when the UBCOM was unable to catch up with the LBCOM.  The question that could be raised is: �was it really the failure of the UBCOM to catch up with the LBCOM or was it the LBCOM in itself failing to catch up with sliding heel�.  This question is answered through Figure 10 depicting the velocity difference between the sliding heel and the LBCOM for a recovery and fall.  The results indicate that there was a statistically significant difference (P=0.01) between the heel and LBCOM.  This raises the question that should the trailing leg also catch up �quickly� along with the trunk to avoid a fall.  Cham & Redfern (2002) suggested that to resist slip-related falls during walking, the central nervous system (CNS) must reactively modify the resultant moments of the lower limbs that can provide stability recovery while support upright posture against gravity.  Thus the role of the lower limbs in itself might be crucial in recovery from a slippery perturbation.  This needs further exploration in the future.  Since the term �quickly� was introduced the next question is how quick is quick enough to avoid a fall?
<INSERT FIGURE 10 HERE>
	The results from the study suggest that there is possibly a threshold value of 0.4m/s in terms of difference in velocities between the LBCOM and the UBCOM beyond which individuals could fall.  This supports the second hypothesis in the study.  This novel approach to exploring the biomechanics of slips and falls using the LBCOM and the UBCOM dynamics appears to be intuitive in that if the upper body or the lower body moves faster than the other by a certain value a fall could result.  Thus this approach could be an alternative to the traditional approach using the WBCOM and the BOS as suggested by You et al. (2001).
	Next, it was hypothesized that older fallers would have a higher difference in velocity values between the UBCOM and the LBCOM when compared to the younger fallers.  It was also hypothesized that younger non-fallers would have a higher difference in velocity values between the UBCOM and the LBCOM when compared to the older non-fallers.  Both of the aforementioned cases were found to be true.  These findings suggest that elderly individuals are unable to use a successful �catch up� strategy and maintain a relatively lower difference in velocity between the LBCOM and the UBCOM resulting in their higher incidence of falls.  On the other hand, younger individuals who recover have the ability to maintain a higher difference in velocities between the LBCOM and the UBCOM, and still recover.  In other words, older individuals who recover might be able to do so only for a smaller difference in velocities between the LBCOM and the UBCOM when compared to younger individuals.  These findings clearly indicate that elderly individuals are unable to react to slippery perturbations like the younger individuals.
	One benefit from using this novel approach to studying the biomechanics of slips and falls in the elderly is that no force plate is required.  Only kinematic data using reflective markers placed on different segments on the upper and lower body could be used to determine the LBCOM and the UBCOM to better understand the dynamics of slips and falls.  The second benefit of using this approach is that it breaks away from the traditional approach of using the WBCOM and the BOS, by introducing the upper and lower body dynamics to better understand the biomechanics of slips and falls.  The third possible benefit is that the study proposes looking at fallers and non-fallers by associating them with young and elderly individuals.  It might be even more important to understand recovery (non-fallers) when compared to falls and to understand this difference across age groups.
	 Future research should explore if this approach of the UBCOM-LBCOM dynamics is transferable to different scenarios.  Does it provide useful insight for load carrying biomechanics for instance?  If individuals are not carrying any load, would that enable them to have a larger difference in velocities between the LBCOM and the UBCOM and still recover?  Another possible direction could be to investigate whether elderly individuals who participate in an exercise program like Tai-Chi, which involves coordinated upper and lower body movements, are able to maintain a smaller difference in velocities between the LBCOM and the UBCOM when they encounter a slippery perturbation, and thus reduce their likelihood of a slip-induced fall.  
Conclusion	

	This study demonstrates that a single variable such as a velocity difference between the LBCOM and UBCOM could be used to better understand the biomechanics of slips and falls in the elderly.  The results from the study suggest that older individuals could benefit from training or exercise programs that could help them move their upper body more quickly with respect to their lower body when they encounter a slippery surface.












Acknowledgements

No external funding was used to support this study.  All the subjects volunteered to participate in the study. The motion analysis system at the ergo lab in the Industrial Engineering Department was used for the study.

Conflict of Interest

There is no conflict of interest

References

Cham, R., and Redfern, M. S. (2001) Lower extremity corrective reactions to slip events. Journal 	of Biomechanics, 34, 1439�1445.

Lockhart, T. E., Woldstad, J. C. and Smith J. L. (2003).  Effects of age-related gait 
changes on the biomechanics of slips and falls.  Ergonomics, 46 (12), 1136-1160.

Lockhart, T. E. (2000). Effects of musculoskeletal and sensory degradation due to age on 
the biomechanics of slips and falls.  Ph.D. dissertation, Department of Industrial 
Engineering, Texas Tech University, USA.

Marigold, D. S., Bethune, A. J. and Patla, A. E. (2003). Role of the unperturbed limb and
	arms in reactive recovery response to an unexpected slip during locomotion.
	Journal of Nuerophysiology, 89, 1727-1737.

Troy, K.L., Donovan, S. J. and Grabiner, M. D. (2009).  Theoretical contribution of the upper 	extremities to reducing trunk extension following a laboratory-induced slip.  Journal of 	Biomechanics, 42, 1339-1344.

Winter, D. A. (2005).  Biomechanics and motor control of human movement (3rd edn).  
Hoboken, NJ: John Wiley & Sons, Inc., 9-10.  

Winter, D. A. (1991).  Biomechanics and motor control of human gait (2nd edn).  
Waterloo, Canada: University of Waterloo Press, 17-70.  

You, J., Chou, Y., Lin C. and Su, F. (2001).  Effect of slip on movement of body center 
	of mass relative to base of support.  Clinical Biomechanics, 16, 167-173.











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