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Exoskeleton plantarflexion assistance for elderly
Gait & Posture 52 (2017) 183–188
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Full length article
Exoskeleton plantarflexion assistance for elderly S. Gallea,* , W. Deravea , F. Bossuyta , P. Caldersb , P. Malcolma,c , D. De Clercqa a
Department of Movement and Sport Sciences, Ghent University, Watersportlaan 2, B-9000 Ghent, Belgium Department of Physical Therapy and Motor Rehabilitation, De Pintelaan 185, B-9000 Ghent, Belgium c Department of Biomechanics, University of Nebraska at Omaha, Omaha, NE, 68182, United States b
A R T I C L E I N F O
Article history: Received 27 May 2015 Received in revised form 20 September 2016 Accepted 25 November 2016 Keywords: Exoskeleton Elderly Walking Plantarflexion assistance Metabolic cost
A B S T R A C T
Elderly are confronted with reduced physical capabilities and increased metabolic energy cost of walking. Exoskeletons that assist walking have the potential to restore walking capacity by reducing the metabolic cost of walking. However, it is unclear if current exoskeletons can reduce energy cost in elderly. Our goal was to study the effect of an exoskeleton that assists plantarflexion during push-off on the metabolic energy cost of walking in physically active and healthy elderly. Seven elderly (age 69.3 3.5 y) walked on treadmill (1.11 m s2) with normal shoes and with the exoskeleton both powered (with assistance) and powered-off (without assistance). After 20 min of habituation on a prior day and 5 min on the test day, subjects were able to walk with the exoskeleton and assistance of the exoskeleton resulted in a reduction in metabolic cost of 12% versus walking with the exoskeleton powered-off. Walking with the exoskeleton was perceived less fatiguing for the muscles compared to normal walking. Assistance resulted in a statistically nonsignificant reduction in metabolic cost of 4% versus walking with normal shoes, likely due to the penalty of wearing the exoskeleton powered-off. Also, exoskeleton mechanical power was relatively low compared to previously identified optimal assistance magnitude in young adults. Future exoskeleton research should focus on further optimizing exoskeleton assistance for specific populations and on considerate integration of exoskeletons in rehabilitation or in daily life. As such, exoskeletons should allow people to walk longer or faster than without assistance and could result in an increase in physical activity and resulting health benefits. © 2016 Elsevier B.V. All rights reserved.
1. Introduction Plantarflexion assisting exoskeletons can reduce the metabolic energy cost of walking [1–3], improve performance [4], increase walking speed [5] or restore function in impaired subjects [6]. Mobility assistance in daily life is becoming a realistic option due to the development of autonomous exoskeletons. The latter reduce metabolic cost during walking using passive mechanisms without external energy input [1] or while carrying all the hardware and power sources [3,7]. A next challenge is to identify specific populations for which an exoskeleton can improve quality of life and to evaluate both the immediate and long-term effects of exoskeleton assistance in these populations. While exoskeletons could counter gait impairments (e.g. [6]), the reduction in the metabolic cost itself could also be beneficial
* Corresponding author. E-mail addresses: [email protected] (S. Galle), [email protected] (W. Derave), [email protected] (F. Bossuyt), [email protected] (P. Calders), [email protected] (P. Malcolm), [email protected] (D. De Clercq). http://dx.doi.org/10.1016/j.gaitpost.2016.11.040 0966-6362/© 2016 Elsevier B.V. All rights reserved.
for certain populations. With age, metabolic cost of walking increases [8], while maximal aerobic power [9] and physical capabilities decline [10]. This may lead to a vicious circle of limited performance in daily life activities, less physical activity and reduced cardiorespiratory fitness. Low cardiorespiratory fitness is a predictor of mortality risk in elderly [11] but can be improved by performing physical activity, also in sedentary elderly [12]. As the aerobic reserves during walking are related to reduced walking speed in elderly [13], a reduction in the energy cost of walking could increase walking speed or walking duration while maintaining a comfortable aerobic reserve. On the long term, walking assistance with an exoskeleton could improve walking mobility and physical activity, similar to the assumed positive effect of electrical bicycles on meeting physical activity guidelines for sedentary people [14]. A first step to explore the potential of improving physical activity and quality of life with exoskeleton assistance is to study the acute effect of exoskeleton walking in healthy elderly that experience normal age-related biological degeneration. Although Norris et al. [5] showed that elderly can walk with a plantarflexion assisting exoskeleton, the effect on the metabolic cost was
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inconclusive due to their low number of subjects. Also, as the amount of assistance is an important determinant of the metabolic cost of exoskeleton walking [15], assistance magnitude might have been insufficient. It is important to first focus on healthy elderly before pathological gait can be tackled to identify possible limitations of exoskeleton walking in elderly. Our ankle exoskeleton reduces metabolic cost with 12% [15] versus normal walking in a population of young adults but it is unclear how elderly will perform due to reduced physical function [9,10] and potential deviations from normal gait that come with age [16,17]. Our goal was to study if healthy elderly (age 65 or more) could benefit from exoskeleton assistance by studying the effect of a plantarflexion assisting exoskeleton during walking, with particular focus on the metabolic energy cost. 2. Methods 2.1. Subjects Eight physically active participants without treadmill nor exoskeleton walking experience signed an informed consent, approved by the ethical committee of the Ghent University Hospital and completed the short self-administered International Physical Activity Questionnaire (IPAQ) [18]. Data from one subject were excluded because deviated walking kinematics of that subject resulted in exoskeleton malfunction (Electronic Supplementary material), resulting in an experimental population of 7 subjects (6 male, 1 female; age 69.3 3.5 y; body mass 73.1 6.9 kg; stature 170.4 6.2 cm). 2.2. Exoskeleton Subjects walked with bilateral ankle-foot exoskeletons that assisted plantarflexion during push-off. More details can be found in previous publications [2,4,15,19]. In a previous study [15] in young female adults we identified optimal assistance timing and power magnitude. The participants of that study reported an early actuation onset and high amounts of exoskeleton power as uncomfortable. To avoid discomfort in the older population, we used assistance parameters similar to those that previously resulted in the highest comfort scores in young female adults [15]: actuation onset at 49 1% of stride, actuation ending coinciding with toe-off (68% of stride) and average positive exoskeleton ankle joint mechanical power during a stride of 0.11 0.2 W kg 1 per leg. Findings of the exoskeleton condition with similar assistance parameters from the experiment in young female adults [15] were added to the results for illustrative purposes.
POW1 for the first and POW2 for the second powered condition). Conditions were performed in semi-randomized order (SHOES was always first or last due to the required time to don and doff the exoskeleton). It was chosen to do the powered condition twice as pilot testing showed that the metabolic energy cost can be increased in the first minutes of powered locomotion, probably because habituation from the previous day is not fully retained. 2.4. Data collection Oxygen consumption and carbon dioxide production were measured continuously (K4b2, Cosmed, Rome, Italy). A linear displacement sensor (100 Hz; SLS130, Penny&Giles, Christchurch, UK) was connected between the foot and shank segment of the exoskeleton (Fig. 1). Based on a prior three-dimensional calibration with motion analysis, ankle joint angle and moment arm of the pneumatic muscle force were measured with the linear displacement sensor. A load cell (100 Hz; 210 Series, Richmond Industries Ltd., Reading, UK) was used to measure pneumatic muscle force. As the left load cell got damaged during the experiment, results of the right leg only were shown for ankle kinematics and exoskeleton kinetics. Consumer camera’s (30 Hz; HDR-CX240E, Sony, Weybridge, UK) were used to collect dorsal images. After each trial, subjects scored perception of the condition on a visual analog scale (VAS) [20]. Difficulty was scored between ‘much more difficult’ and ‘much easier’ compared to the reference condition. Subjects scored difficulty of walking with normal shoes on the treadmill compared to over ground. Difficulty of powered and powered-off exoskeleton walking was scored compared to walking with normal shoes on the treadmill. In the same way powered exoskeleton walking was evaluated for comfort from ‘much less comfortable’ to ‘much more comfortable’, overall fatigue and leg muscle fatigue from ‘much less tiring’ to ‘much more tiring’ and balance from ‘much worse’ to ‘much better’, all compared to walking with normal shoes on treadmill. 2.5. Data analysis IPAQ was used to classify activity level as low, moderate or high [18]. The metabolic energy cost, measured as net metabolic power, was calculated with the formula of Brockway for the last two minutes of each interval, divided by bodyweight and diminished
2.3. Experimental design Subjects performed two walking protocols on two separate days with maximum one week in between, one for habituation and one for data collection. On the habituation day they performed six trials of five minutes with three minutes of rest in between on a treadmill. First, they walked with normal shoes at a speed of 0.83 m s 1, which was increased with 0.14 m s 1 each minute until 1.11 m s 1. All other conditions were done at a speed of 1.11 m s 1: walking with the exoskeleton powered-off (without assistance of the pneumatic muscles) and four trials walking with the powered exoskeleton (with assistance of the pneumatic muscles) to allow habituation [19]. On the data collection day, subjects did a four minutes standing rest trial, followed by four walking trials of five minutes with three minutes of rest in between. Subjects walked with normal shoes (SHOES), with the exoskeleton powered-off (OFF) and twice with the powered exoskeleton (referred to as
Fig. 1. Ankle-foot exoskeleton. Representation of the ankle-foot exoskeleton with pneumatic muscles at the dorsal side, a load cell to calculate pneumatic muscle force, a linear displacement sensor to calculate ankle joint angle and moment arm of the pneumatic muscle and a footswitch to detect foot contact. Exoskeletons were worn on both legs during walking and assisted plantarflexion during push-off.
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POW2 (3.12 0.40 W kg 1; P = 0.01; ES = 1.10) were reduced with respectively 9.5 6.1% and 12.0 6.9% compared to OFF (3.55 0.38 W kg 1). Net metabolic power for OFF was 9.8 8.0% higher compared to SHOES (3.24 0.36 W kg 1; P = 0.02; ES = 0.84) (Fig. 2). No significant difference was found between SHOES and POW1 (P = 0.90; ES = 0.04) or POW2 (P = 0.23; ES = 0.31) although the average reduction was respectively 1 and 4%. Physical activity level was moderate or high for all subjects. During POW1 and POW2 the exoskeleton delivered a plantarflexion torque, which resulted in positive exoskeleton power during the push-off (Fig. 3). Ankle angular velocity, exoskeleton torque and exoskeleton mechanical power were very similar for POW1 and POW2 (Fig. 3). No significant differences were found for peak exoskeleton power (P = 0.644; ES = 0.09) or average power (P = 0.976; ES = 0.01)
Fig. 2. Net metabolic cost. Bars with standard deviations represent net metabolic power for the four walking conditions: walking with normal shoes without an exoskeleton (SHOES), walking with the exoskeleton without assistance of the pneumatic muscles (OFF), the first condition walking with the powered exoskeleton (POW1) and the second condition walking with the powered exoskeleton (POW2). Repeated measures ANOVA with post-hoc tests (LSD) was done to compare net metabolic power between conditions. * indicate a statistically significant difference between conditions (P 0.05).
with metabolic power of the standing rest trial (e.g. [2,19]). MaxTraq software (Innovasion Systems, Columbiaville, Michigan, USA) was used to analyze video images to calculate step length (time between consecutive heel contacts multiplied with walking speed) and step width (distance between the middle of the left and right heel during stance [21]). Step length and step width were averaged over the last two minutes of each condition and intrasubject variability was calculated as the standard deviation of consecutive steps in the last two minutes of each condition. Load cell data and displacement sensor data were filtered with a second order low pass filter (cut-off 12 Hz) in Matlab (MathWorks Inc., Natick, Massachusetts, USA). Exoskeleton torque was calculated by multiplying pneumatic muscle force (divided by body mass) with moment arm length. Exoskeleton mechanical power was calculated by multiplying exoskeleton torque with ankle joint angular velocity. These variables were time-normalized from heel contact to heel contact and averaged over the last two minutes of the conditions. Average positive exoskeleton mechanical power was calculated by numerical integration of the positive exoskeleton mechanical power bursts, divided by stride time. 2.6. Statistics Statistics were done with SPSS Statistics 21 (IBM, Armonk, NY, USA). Repeated measures ANOVA (significance threshold, P 0.05) with post-hoc tests (Least Significant Difference) were used to compare data between conditions. Effect sizes (ES) were calculated with Cohen’s d for differences between groups (mean difference between groups divided by the pooled standard deviation) [22]. One-sample t-tests (P 0.05) were used to analyze if perception scores for a given condition differed from zero (=the reference condition). Effect sizes (ES) were calculated with Cohen’s d for differences with zero (mean divided by standard deviation) [22]. 3. Results All subjects but one were able to comfortably walk with the exoskeleton (Electronic Supplementary material). Net metabolic power for POW1 (3.23 0.49 W kg 1; P = 0.01; ES = 0.75) and
Fig. 3. Joint kinematics and exoskeleton kinetics. Thick lines are population means for ankle angular velocity (A), exoskeleton ankle joint torque (B) and exoskeleton mechanical power (C). Curves are normalized for the right leg from heel strike (0%) to heel strike (100%). Thin curves are +1 standard deviation. Data represent the elderly subjects during walking with the exoskeleton without assistance of the pneumatic muscles (OFF), during the first condition walking with the powered exoskeleton (POW1) and during the second condition walking with the powered exoskeleton (POW2). Reference data from a previous experiment [15] in which 10 young female subjects walked with an exoskeleton with a similar exoskeleton mechanical power profile (REF) are added for illustrative purpose.
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Table 1 Exoskeleton kinetics and temporal parameters.
1
Peak exoskeleton mech. power (W kg ) Average pos. exoskeleton mech. power per stride (W kg Step length (m) Step length variability (m) Step width (m) Step width variability (m)
1
)
SHOES
OFF
POW1
POW2
/ / 0.59 0.04 0.04 0.01 0.10 0.02 0.02 0.00
0.02 0.00 0.00 0.00 0.59 0.03 0.04 0.01 0.10 0.01 0.02 0.00
1.13 0.16* 0.11 0.02* 0.61 0.05* 0.04 0.01 0.10 0.02 0.02 0.01
1.13 0.16* 0.11 0.02* 0.62 0.05*,** 0.04 0.01 0.09 0.01 0.02 0.01
Mean values for exoskeleton power and temporal parameters. Conditions refer to walking with normal shoes without an exoskeleton (SHOES), walking with the exoskeleton without assistance of the pneumatic muscles (OFF), the first condition walking with the powered exoskeleton (POW1) and the second condition walking with the powered exoskeleton (POW2). Peak and average exoskeleton mechanical power are based on the mechanical power of the exoskeleton of the right leg because the load cell of the left leg got damaged during the experiment. Temporal parameters are the mean values for step length and step width for the last two minutes of each condition. Step length and step width variability are the averages of the standard deviation of the consecutive steps in the last two minutes of each condition for respectively step length and step width. Repeated measures ANOVA was used to compare between conditions. * indicate a statistically significant difference from OFF, ** indicate a statistically significant difference from SHOES (P 0.05).
between POW1 and POW2 (Table 1). Exoskeleton assistance increased step length in POW1 (P = 0.04; ES = 0.38) and POW2 (P = 0.01; ES = 0.73) compared to OFF (Table 1). Step length was also increased for POW2 compared to SHOES (P = 0.02; ES = 0.67) (Table 1). Walking with the exoskeleton in the OFF condition was perceived more difficult compared to the reference condition, which was walking with normal shoes on treadmill (P = 0.05; ES = 0.92) (Fig. 4). Walking with the powered exoskeleton was not perceived as more difficult compared to the reference condition, which was walking with normal shoes on treadmill (POW1: P = 0.462; ES = 0.30/POW2: P = 0.481, ES = 0.28). Walking in POW2 was perceived to cause less fatigue in the legs compared to the reference condition, which was walking with normal shoes on the treadmill (P = 0.05; ES = 0.91). All other comparisons did not reach statistical significance. In a previous experiment [15] young female adults walked with similar exoskeleton assistance compared to the current study in elderly (Fig. 3). Angular velocity was lower during the push-off in the elderly, while pneumatic muscle force was higher. This resulted in a similar exoskeleton mechanical power pattern for both populations. In the younger population, assistance of the exoskeleton resulted in a reduction in metabolic cost of 15.5 5.0% (P = 0.01; ES = 0.95) versus powered-off walking and a trend towards a significant reduction of 5.9 8.5% (P = 0.07; ES = 0.39) versus walking with standard shoes. 4. Discussion The goal of this study was to investigate the effect of walking with an exoskeleton in healthy elderly individuals. Assistance of the exoskeleton resulted in a reduction in metabolic cost of 12% versus walking with the exoskeleton powered-off after a habituation of 20 min on a prior day and 5 min on the test day. Assistance of the exoskeleton was also perceived to reduce less muscle fatigue compared to normal walking. The metabolic reductions versus walking with normal shoes were much lower due to the metabolic penalty of wearing the powered-off exoskeleton. This increase in metabolic cost of 10% is similar to our previous studies [2,15,19] and caused by the additional weight of the exoskeleton and potential movement restrictions. On average, a reduction of 4% in metabolic cost was found between powered walking (POW2) and walking with normal shoes, although not statistically significant. In a previous study of Norris et al. [5], the limited number of subjects did not allow statistical comparisons between metabolic cost of powered and powered-off exoskeleton walking in healthy elderly. Based on their results, a reduction of around 4% in the metabolic cost could be expected for powered versus powered-off exoskeleton walking [5]. Despite differences in subjects,
Fig. 4. Perception measures. Horizontal bars show the perception of difficulty for walking with normal shoes on treadmill (SHOES) compared to a reference condition, which was walking with normal shoes over ground. Perception of difficulty is also shown for walking with the exoskeleton without assistance of the pneumatic muscles (OFF), the first condition walking with the powered exoskeleton (POW1) and the second condition walking with the powered exoskeleton (POW2) compared to a reference condition, which was walking with normal shoes on treadmill (SHOES). Other measures show the perception of pleasantness, fatigue (for the muscles), fatigue (overall) and balance for POW1 and POW2 compared to the reference condition, which was walking with normal shoes on treadmill (SHOES). A negative score represents “worse” compared to the reference condition, a positive score represents ‘better’ compared to the reference condition. Independent samples t-test was used to compare the perception with the reference condition (score = 0). * indicate a statistically significant difference with 0 (P 0.05).
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habituation, exoskeleton design and control, the exoskeleton power magnitude seems the major cause for the higher reduction that was found in our results. Peak mechanical power of the exoskeleton in their study (0.46 0.12 W kg 1) was only 41% of the peak mechanical power in our study and we previously showed that the power magnitude is crucial in reducing the metabolic cost [15]. The next step would be to evaluate if healthy elderly could also comfortably walk with the power magnitude that is metabolically optimal for young adults [15] (i.e., almost twice the amount of power delivered to the elderly in the current study). We compared our results with data of 10 young female adults who walked with the same exoskeleton with similar exoskeleton assistance parameters in a previous experiment of our group [15]. In that study, we found only slightly higher reductions in metabolic energy cost (-16% versus powered-off and 5% versus walking with normal shoes). In the younger population, doubling the amount of exoskeleton power increased reductions in metabolic cost to 21% versus powered-off walking and 12% versus walking with normal shoes [15]. If elderly are able to walk with more exoskeleton power, this could consequently lead to higher reductions in metabolic cost. Gait of elderly is characterized by reduced walking speed, reduced step length, and reduced balance [16,23]. Also, variations in step length and step width have been related to falls and mobility problems [24]. Although stability was previously suggested to be a limiting factor in the application of exoskeletons [25], our population did not perceive the exoskeleton as disturbing their balance compared to walking with normal shoes. This was supported with no alterations in step width and variability in step length and step width in the exoskeleton conditions. The good physical capabilities of our test population were emphasized by their ability to walk comfortably on the treadmill within 5 min, without holding the handrails, while normal habituation to treadmill walking takes up to 14 min [26]. In future exoskeleton experiments with weaker populations, equilibriometric tests [23] in combination with balance and symmetry measurements during locomotion [17,25] could be used to distinguish if balance is a major limitation for exoskeleton assistance in weaker populations, also during over ground walking, with variations in speed or direction and on uneven terrain. Exoskeletons have the potential to improve quality of life by improving locomotion abilities, also for elderly that suffer from increased energetic cost of daily life activities [13] in combination with reduced physical function [9,10]. An exoskeleton could allow to improve walking speed [5] and walking duration and as such allow to increase the total amount of physical activity [11,12]. This could also help other populations with reduced exercise tolerance as subjects with Chronic Obstructive Pulmonary Disease whom frequently experience ventilatory limitations when performing activities of daily living, resulting in peripheral muscle weakness and physical inactivity [27]. In general, our results seem promising for the use of exoskeletons as a potential rehabilitation tool or for daily life assistance in the future. However, when thinking about future applications we should pay attention to a thoughtful integration of exoskeletons in such a way that they improve rather than reduce overall physical activity. This could be achieved by allowing subjects to walk longer and faster than they did before. The latter could be particularly important for ankle-foot exoskeletons in elderly often experiencing plantarflexor weakness and reduced ankle power generation [16,28]. Ankle exoskeletons assistance of the weakened plantarflexors (e.g. [2,15,19]) could as such improve walking efficiency. The reported increased step length during exoskeleton walking could be a sign into that direction. We previously showed that the activity of the plantarflexors, together with other leg muscles, is only reduced to a limited extent [15,29]. However, it is important to acknowledge the
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risk of ‘accelerated’ sarcopenia. Increasing walking speed or walking duration could be suggested in order to maintain or improve the total load for important leg muscles similar to the load during normal walking. Our exoskeleton has several limitations, especially for gait assistance in specific populations. Reducing the weight and the design of the exoskeleton in accordance to recent exoskeletons [1,3] could reduce the penalty of wearing the exoskeleton from 10% to less than 3%, even for autonomous devices. This suggests that reductions of more than 10% versus walking with normal shoes may be possible in healthy and physically active elderly by improvements in design of the exoskeleton only. Also, one subject was not able to walk comfortably with the exoskeleton (Electronic Supplementary material) due to knee flexion during stance, which perturbed exoskeleton assistance. This highlights the drawback of using a single assistance pattern that is not directly related to the user ‘s gait characteristics. For populations where individual differences are bigger, it will be important to gradually adapt exoskeleton assistance to the needs of each subject, for example by using myoelectric controllers [30]. On average, all perception scores were better and metabolic cost was lower in the second powered condition compared to the first powered condition, suggesting that habituation was not yet complete after the first powered condition. Longer habituation could potentially lead to bigger reductions in metabolic cost of walking. Since the good fitness and the high physical activity of our subjects might have influenced our results, future research with exoskeletons in elderly or patient populations could include physical activity and physical fitness as possible determinants for the effect of exoskeleton assistance. Also, a true comparison between exoskeleton walking in young adults and in elderly could further reveal differences and limitations for assistance in elderly. In conclusion, healthy and physically active elderly were able to walk with an ankle-foot exoskeleton that assisted plantarflexion during the push-off. This caused a reduction in metabolic cost versus powered-off exoskeleton walking. Although no statistically significant difference was found between powered exoskeleton walking and normal walking, improvements in design and more exoskeleton power should result in a reduction versus normal walking. As our subjects had good physical capabilities and were very physically active, it is hard to generalize our results to weaker elderly or other patient populations. Nevertheless, our results in healthy and physically active elderly are promising for future applications for exoskeletons as a tool to improve walking capacity in specific populations. Conflict of interest None. Acknowledgements The authors wish to thank Aqtor! for constructing the exoskeleton and Ing. Spiessens D. for the technical support. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j. gaitpost.2016.11.040. References [1] S.H. Collins, M.B. Wiggin, G.S. Sawicki, Reducing the energy cost of human walking using an unpowered exoskeleton, Nature 522 (2015) 212–215, doi: http://dx.doi.org/10.1038/nature14288.
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Full length article
Exoskeleton plantarflexion assistance for elderly S. Gallea,* , W. Deravea , F. Bossuyta , P. Caldersb , P. Malcolma,c , D. De Clercqa a
Department of Movement and Sport Sciences, Ghent University, Watersportlaan 2, B-9000 Ghent, Belgium Department of Physical Therapy and Motor Rehabilitation, De Pintelaan 185, B-9000 Ghent, Belgium c Department of Biomechanics, University of Nebraska at Omaha, Omaha, NE, 68182, United States b
A R T I C L E I N F O
Article history: Received 27 May 2015 Received in revised form 20 September 2016 Accepted 25 November 2016 Keywords: Exoskeleton Elderly Walking Plantarflexion assistance Metabolic cost
A B S T R A C T
Elderly are confronted with reduced physical capabilities and increased metabolic energy cost of walking. Exoskeletons that assist walking have the potential to restore walking capacity by reducing the metabolic cost of walking. However, it is unclear if current exoskeletons can reduce energy cost in elderly. Our goal was to study the effect of an exoskeleton that assists plantarflexion during push-off on the metabolic energy cost of walking in physically active and healthy elderly. Seven elderly (age 69.3 3.5 y) walked on treadmill (1.11 m s2) with normal shoes and with the exoskeleton both powered (with assistance) and powered-off (without assistance). After 20 min of habituation on a prior day and 5 min on the test day, subjects were able to walk with the exoskeleton and assistance of the exoskeleton resulted in a reduction in metabolic cost of 12% versus walking with the exoskeleton powered-off. Walking with the exoskeleton was perceived less fatiguing for the muscles compared to normal walking. Assistance resulted in a statistically nonsignificant reduction in metabolic cost of 4% versus walking with normal shoes, likely due to the penalty of wearing the exoskeleton powered-off. Also, exoskeleton mechanical power was relatively low compared to previously identified optimal assistance magnitude in young adults. Future exoskeleton research should focus on further optimizing exoskeleton assistance for specific populations and on considerate integration of exoskeletons in rehabilitation or in daily life. As such, exoskeletons should allow people to walk longer or faster than without assistance and could result in an increase in physical activity and resulting health benefits. © 2016 Elsevier B.V. All rights reserved.
1. Introduction Plantarflexion assisting exoskeletons can reduce the metabolic energy cost of walking [1–3], improve performance [4], increase walking speed [5] or restore function in impaired subjects [6]. Mobility assistance in daily life is becoming a realistic option due to the development of autonomous exoskeletons. The latter reduce metabolic cost during walking using passive mechanisms without external energy input [1] or while carrying all the hardware and power sources [3,7]. A next challenge is to identify specific populations for which an exoskeleton can improve quality of life and to evaluate both the immediate and long-term effects of exoskeleton assistance in these populations. While exoskeletons could counter gait impairments (e.g. [6]), the reduction in the metabolic cost itself could also be beneficial
* Corresponding author. E-mail addresses: [email protected] (S. Galle), [email protected] (W. Derave), [email protected] (F. Bossuyt), [email protected] (P. Calders), [email protected] (P. Malcolm), [email protected] (D. De Clercq). http://dx.doi.org/10.1016/j.gaitpost.2016.11.040 0966-6362/© 2016 Elsevier B.V. All rights reserved.
for certain populations. With age, metabolic cost of walking increases [8], while maximal aerobic power [9] and physical capabilities decline [10]. This may lead to a vicious circle of limited performance in daily life activities, less physical activity and reduced cardiorespiratory fitness. Low cardiorespiratory fitness is a predictor of mortality risk in elderly [11] but can be improved by performing physical activity, also in sedentary elderly [12]. As the aerobic reserves during walking are related to reduced walking speed in elderly [13], a reduction in the energy cost of walking could increase walking speed or walking duration while maintaining a comfortable aerobic reserve. On the long term, walking assistance with an exoskeleton could improve walking mobility and physical activity, similar to the assumed positive effect of electrical bicycles on meeting physical activity guidelines for sedentary people [14]. A first step to explore the potential of improving physical activity and quality of life with exoskeleton assistance is to study the acute effect of exoskeleton walking in healthy elderly that experience normal age-related biological degeneration. Although Norris et al. [5] showed that elderly can walk with a plantarflexion assisting exoskeleton, the effect on the metabolic cost was
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inconclusive due to their low number of subjects. Also, as the amount of assistance is an important determinant of the metabolic cost of exoskeleton walking [15], assistance magnitude might have been insufficient. It is important to first focus on healthy elderly before pathological gait can be tackled to identify possible limitations of exoskeleton walking in elderly. Our ankle exoskeleton reduces metabolic cost with 12% [15] versus normal walking in a population of young adults but it is unclear how elderly will perform due to reduced physical function [9,10] and potential deviations from normal gait that come with age [16,17]. Our goal was to study if healthy elderly (age 65 or more) could benefit from exoskeleton assistance by studying the effect of a plantarflexion assisting exoskeleton during walking, with particular focus on the metabolic energy cost. 2. Methods 2.1. Subjects Eight physically active participants without treadmill nor exoskeleton walking experience signed an informed consent, approved by the ethical committee of the Ghent University Hospital and completed the short self-administered International Physical Activity Questionnaire (IPAQ) [18]. Data from one subject were excluded because deviated walking kinematics of that subject resulted in exoskeleton malfunction (Electronic Supplementary material), resulting in an experimental population of 7 subjects (6 male, 1 female; age 69.3 3.5 y; body mass 73.1 6.9 kg; stature 170.4 6.2 cm). 2.2. Exoskeleton Subjects walked with bilateral ankle-foot exoskeletons that assisted plantarflexion during push-off. More details can be found in previous publications [2,4,15,19]. In a previous study [15] in young female adults we identified optimal assistance timing and power magnitude. The participants of that study reported an early actuation onset and high amounts of exoskeleton power as uncomfortable. To avoid discomfort in the older population, we used assistance parameters similar to those that previously resulted in the highest comfort scores in young female adults [15]: actuation onset at 49 1% of stride, actuation ending coinciding with toe-off (68% of stride) and average positive exoskeleton ankle joint mechanical power during a stride of 0.11 0.2 W kg 1 per leg. Findings of the exoskeleton condition with similar assistance parameters from the experiment in young female adults [15] were added to the results for illustrative purposes.
POW1 for the first and POW2 for the second powered condition). Conditions were performed in semi-randomized order (SHOES was always first or last due to the required time to don and doff the exoskeleton). It was chosen to do the powered condition twice as pilot testing showed that the metabolic energy cost can be increased in the first minutes of powered locomotion, probably because habituation from the previous day is not fully retained. 2.4. Data collection Oxygen consumption and carbon dioxide production were measured continuously (K4b2, Cosmed, Rome, Italy). A linear displacement sensor (100 Hz; SLS130, Penny&Giles, Christchurch, UK) was connected between the foot and shank segment of the exoskeleton (Fig. 1). Based on a prior three-dimensional calibration with motion analysis, ankle joint angle and moment arm of the pneumatic muscle force were measured with the linear displacement sensor. A load cell (100 Hz; 210 Series, Richmond Industries Ltd., Reading, UK) was used to measure pneumatic muscle force. As the left load cell got damaged during the experiment, results of the right leg only were shown for ankle kinematics and exoskeleton kinetics. Consumer camera’s (30 Hz; HDR-CX240E, Sony, Weybridge, UK) were used to collect dorsal images. After each trial, subjects scored perception of the condition on a visual analog scale (VAS) [20]. Difficulty was scored between ‘much more difficult’ and ‘much easier’ compared to the reference condition. Subjects scored difficulty of walking with normal shoes on the treadmill compared to over ground. Difficulty of powered and powered-off exoskeleton walking was scored compared to walking with normal shoes on the treadmill. In the same way powered exoskeleton walking was evaluated for comfort from ‘much less comfortable’ to ‘much more comfortable’, overall fatigue and leg muscle fatigue from ‘much less tiring’ to ‘much more tiring’ and balance from ‘much worse’ to ‘much better’, all compared to walking with normal shoes on treadmill. 2.5. Data analysis IPAQ was used to classify activity level as low, moderate or high [18]. The metabolic energy cost, measured as net metabolic power, was calculated with the formula of Brockway for the last two minutes of each interval, divided by bodyweight and diminished
2.3. Experimental design Subjects performed two walking protocols on two separate days with maximum one week in between, one for habituation and one for data collection. On the habituation day they performed six trials of five minutes with three minutes of rest in between on a treadmill. First, they walked with normal shoes at a speed of 0.83 m s 1, which was increased with 0.14 m s 1 each minute until 1.11 m s 1. All other conditions were done at a speed of 1.11 m s 1: walking with the exoskeleton powered-off (without assistance of the pneumatic muscles) and four trials walking with the powered exoskeleton (with assistance of the pneumatic muscles) to allow habituation [19]. On the data collection day, subjects did a four minutes standing rest trial, followed by four walking trials of five minutes with three minutes of rest in between. Subjects walked with normal shoes (SHOES), with the exoskeleton powered-off (OFF) and twice with the powered exoskeleton (referred to as
Fig. 1. Ankle-foot exoskeleton. Representation of the ankle-foot exoskeleton with pneumatic muscles at the dorsal side, a load cell to calculate pneumatic muscle force, a linear displacement sensor to calculate ankle joint angle and moment arm of the pneumatic muscle and a footswitch to detect foot contact. Exoskeletons were worn on both legs during walking and assisted plantarflexion during push-off.
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POW2 (3.12 0.40 W kg 1; P = 0.01; ES = 1.10) were reduced with respectively 9.5 6.1% and 12.0 6.9% compared to OFF (3.55 0.38 W kg 1). Net metabolic power for OFF was 9.8 8.0% higher compared to SHOES (3.24 0.36 W kg 1; P = 0.02; ES = 0.84) (Fig. 2). No significant difference was found between SHOES and POW1 (P = 0.90; ES = 0.04) or POW2 (P = 0.23; ES = 0.31) although the average reduction was respectively 1 and 4%. Physical activity level was moderate or high for all subjects. During POW1 and POW2 the exoskeleton delivered a plantarflexion torque, which resulted in positive exoskeleton power during the push-off (Fig. 3). Ankle angular velocity, exoskeleton torque and exoskeleton mechanical power were very similar for POW1 and POW2 (Fig. 3). No significant differences were found for peak exoskeleton power (P = 0.644; ES = 0.09) or average power (P = 0.976; ES = 0.01)
Fig. 2. Net metabolic cost. Bars with standard deviations represent net metabolic power for the four walking conditions: walking with normal shoes without an exoskeleton (SHOES), walking with the exoskeleton without assistance of the pneumatic muscles (OFF), the first condition walking with the powered exoskeleton (POW1) and the second condition walking with the powered exoskeleton (POW2). Repeated measures ANOVA with post-hoc tests (LSD) was done to compare net metabolic power between conditions. * indicate a statistically significant difference between conditions (P 0.05).
with metabolic power of the standing rest trial (e.g. [2,19]). MaxTraq software (Innovasion Systems, Columbiaville, Michigan, USA) was used to analyze video images to calculate step length (time between consecutive heel contacts multiplied with walking speed) and step width (distance between the middle of the left and right heel during stance [21]). Step length and step width were averaged over the last two minutes of each condition and intrasubject variability was calculated as the standard deviation of consecutive steps in the last two minutes of each condition. Load cell data and displacement sensor data were filtered with a second order low pass filter (cut-off 12 Hz) in Matlab (MathWorks Inc., Natick, Massachusetts, USA). Exoskeleton torque was calculated by multiplying pneumatic muscle force (divided by body mass) with moment arm length. Exoskeleton mechanical power was calculated by multiplying exoskeleton torque with ankle joint angular velocity. These variables were time-normalized from heel contact to heel contact and averaged over the last two minutes of the conditions. Average positive exoskeleton mechanical power was calculated by numerical integration of the positive exoskeleton mechanical power bursts, divided by stride time. 2.6. Statistics Statistics were done with SPSS Statistics 21 (IBM, Armonk, NY, USA). Repeated measures ANOVA (significance threshold, P 0.05) with post-hoc tests (Least Significant Difference) were used to compare data between conditions. Effect sizes (ES) were calculated with Cohen’s d for differences between groups (mean difference between groups divided by the pooled standard deviation) [22]. One-sample t-tests (P 0.05) were used to analyze if perception scores for a given condition differed from zero (=the reference condition). Effect sizes (ES) were calculated with Cohen’s d for differences with zero (mean divided by standard deviation) [22]. 3. Results All subjects but one were able to comfortably walk with the exoskeleton (Electronic Supplementary material). Net metabolic power for POW1 (3.23 0.49 W kg 1; P = 0.01; ES = 0.75) and
Fig. 3. Joint kinematics and exoskeleton kinetics. Thick lines are population means for ankle angular velocity (A), exoskeleton ankle joint torque (B) and exoskeleton mechanical power (C). Curves are normalized for the right leg from heel strike (0%) to heel strike (100%). Thin curves are +1 standard deviation. Data represent the elderly subjects during walking with the exoskeleton without assistance of the pneumatic muscles (OFF), during the first condition walking with the powered exoskeleton (POW1) and during the second condition walking with the powered exoskeleton (POW2). Reference data from a previous experiment [15] in which 10 young female subjects walked with an exoskeleton with a similar exoskeleton mechanical power profile (REF) are added for illustrative purpose.
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Table 1 Exoskeleton kinetics and temporal parameters.
1
Peak exoskeleton mech. power (W kg ) Average pos. exoskeleton mech. power per stride (W kg Step length (m) Step length variability (m) Step width (m) Step width variability (m)
1
)
SHOES
OFF
POW1
POW2
/ / 0.59 0.04 0.04 0.01 0.10 0.02 0.02 0.00
0.02 0.00 0.00 0.00 0.59 0.03 0.04 0.01 0.10 0.01 0.02 0.00
1.13 0.16* 0.11 0.02* 0.61 0.05* 0.04 0.01 0.10 0.02 0.02 0.01
1.13 0.16* 0.11 0.02* 0.62 0.05*,** 0.04 0.01 0.09 0.01 0.02 0.01
Mean values for exoskeleton power and temporal parameters. Conditions refer to walking with normal shoes without an exoskeleton (SHOES), walking with the exoskeleton without assistance of the pneumatic muscles (OFF), the first condition walking with the powered exoskeleton (POW1) and the second condition walking with the powered exoskeleton (POW2). Peak and average exoskeleton mechanical power are based on the mechanical power of the exoskeleton of the right leg because the load cell of the left leg got damaged during the experiment. Temporal parameters are the mean values for step length and step width for the last two minutes of each condition. Step length and step width variability are the averages of the standard deviation of the consecutive steps in the last two minutes of each condition for respectively step length and step width. Repeated measures ANOVA was used to compare between conditions. * indicate a statistically significant difference from OFF, ** indicate a statistically significant difference from SHOES (P 0.05).
between POW1 and POW2 (Table 1). Exoskeleton assistance increased step length in POW1 (P = 0.04; ES = 0.38) and POW2 (P = 0.01; ES = 0.73) compared to OFF (Table 1). Step length was also increased for POW2 compared to SHOES (P = 0.02; ES = 0.67) (Table 1). Walking with the exoskeleton in the OFF condition was perceived more difficult compared to the reference condition, which was walking with normal shoes on treadmill (P = 0.05; ES = 0.92) (Fig. 4). Walking with the powered exoskeleton was not perceived as more difficult compared to the reference condition, which was walking with normal shoes on treadmill (POW1: P = 0.462; ES = 0.30/POW2: P = 0.481, ES = 0.28). Walking in POW2 was perceived to cause less fatigue in the legs compared to the reference condition, which was walking with normal shoes on the treadmill (P = 0.05; ES = 0.91). All other comparisons did not reach statistical significance. In a previous experiment [15] young female adults walked with similar exoskeleton assistance compared to the current study in elderly (Fig. 3). Angular velocity was lower during the push-off in the elderly, while pneumatic muscle force was higher. This resulted in a similar exoskeleton mechanical power pattern for both populations. In the younger population, assistance of the exoskeleton resulted in a reduction in metabolic cost of 15.5 5.0% (P = 0.01; ES = 0.95) versus powered-off walking and a trend towards a significant reduction of 5.9 8.5% (P = 0.07; ES = 0.39) versus walking with standard shoes. 4. Discussion The goal of this study was to investigate the effect of walking with an exoskeleton in healthy elderly individuals. Assistance of the exoskeleton resulted in a reduction in metabolic cost of 12% versus walking with the exoskeleton powered-off after a habituation of 20 min on a prior day and 5 min on the test day. Assistance of the exoskeleton was also perceived to reduce less muscle fatigue compared to normal walking. The metabolic reductions versus walking with normal shoes were much lower due to the metabolic penalty of wearing the powered-off exoskeleton. This increase in metabolic cost of 10% is similar to our previous studies [2,15,19] and caused by the additional weight of the exoskeleton and potential movement restrictions. On average, a reduction of 4% in metabolic cost was found between powered walking (POW2) and walking with normal shoes, although not statistically significant. In a previous study of Norris et al. [5], the limited number of subjects did not allow statistical comparisons between metabolic cost of powered and powered-off exoskeleton walking in healthy elderly. Based on their results, a reduction of around 4% in the metabolic cost could be expected for powered versus powered-off exoskeleton walking [5]. Despite differences in subjects,
Fig. 4. Perception measures. Horizontal bars show the perception of difficulty for walking with normal shoes on treadmill (SHOES) compared to a reference condition, which was walking with normal shoes over ground. Perception of difficulty is also shown for walking with the exoskeleton without assistance of the pneumatic muscles (OFF), the first condition walking with the powered exoskeleton (POW1) and the second condition walking with the powered exoskeleton (POW2) compared to a reference condition, which was walking with normal shoes on treadmill (SHOES). Other measures show the perception of pleasantness, fatigue (for the muscles), fatigue (overall) and balance for POW1 and POW2 compared to the reference condition, which was walking with normal shoes on treadmill (SHOES). A negative score represents “worse” compared to the reference condition, a positive score represents ‘better’ compared to the reference condition. Independent samples t-test was used to compare the perception with the reference condition (score = 0). * indicate a statistically significant difference with 0 (P 0.05).
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habituation, exoskeleton design and control, the exoskeleton power magnitude seems the major cause for the higher reduction that was found in our results. Peak mechanical power of the exoskeleton in their study (0.46 0.12 W kg 1) was only 41% of the peak mechanical power in our study and we previously showed that the power magnitude is crucial in reducing the metabolic cost [15]. The next step would be to evaluate if healthy elderly could also comfortably walk with the power magnitude that is metabolically optimal for young adults [15] (i.e., almost twice the amount of power delivered to the elderly in the current study). We compared our results with data of 10 young female adults who walked with the same exoskeleton with similar exoskeleton assistance parameters in a previous experiment of our group [15]. In that study, we found only slightly higher reductions in metabolic energy cost (-16% versus powered-off and 5% versus walking with normal shoes). In the younger population, doubling the amount of exoskeleton power increased reductions in metabolic cost to 21% versus powered-off walking and 12% versus walking with normal shoes [15]. If elderly are able to walk with more exoskeleton power, this could consequently lead to higher reductions in metabolic cost. Gait of elderly is characterized by reduced walking speed, reduced step length, and reduced balance [16,23]. Also, variations in step length and step width have been related to falls and mobility problems [24]. Although stability was previously suggested to be a limiting factor in the application of exoskeletons [25], our population did not perceive the exoskeleton as disturbing their balance compared to walking with normal shoes. This was supported with no alterations in step width and variability in step length and step width in the exoskeleton conditions. The good physical capabilities of our test population were emphasized by their ability to walk comfortably on the treadmill within 5 min, without holding the handrails, while normal habituation to treadmill walking takes up to 14 min [26]. In future exoskeleton experiments with weaker populations, equilibriometric tests [23] in combination with balance and symmetry measurements during locomotion [17,25] could be used to distinguish if balance is a major limitation for exoskeleton assistance in weaker populations, also during over ground walking, with variations in speed or direction and on uneven terrain. Exoskeletons have the potential to improve quality of life by improving locomotion abilities, also for elderly that suffer from increased energetic cost of daily life activities [13] in combination with reduced physical function [9,10]. An exoskeleton could allow to improve walking speed [5] and walking duration and as such allow to increase the total amount of physical activity [11,12]. This could also help other populations with reduced exercise tolerance as subjects with Chronic Obstructive Pulmonary Disease whom frequently experience ventilatory limitations when performing activities of daily living, resulting in peripheral muscle weakness and physical inactivity [27]. In general, our results seem promising for the use of exoskeletons as a potential rehabilitation tool or for daily life assistance in the future. However, when thinking about future applications we should pay attention to a thoughtful integration of exoskeletons in such a way that they improve rather than reduce overall physical activity. This could be achieved by allowing subjects to walk longer and faster than they did before. The latter could be particularly important for ankle-foot exoskeletons in elderly often experiencing plantarflexor weakness and reduced ankle power generation [16,28]. Ankle exoskeletons assistance of the weakened plantarflexors (e.g. [2,15,19]) could as such improve walking efficiency. The reported increased step length during exoskeleton walking could be a sign into that direction. We previously showed that the activity of the plantarflexors, together with other leg muscles, is only reduced to a limited extent [15,29]. However, it is important to acknowledge the
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risk of ‘accelerated’ sarcopenia. Increasing walking speed or walking duration could be suggested in order to maintain or improve the total load for important leg muscles similar to the load during normal walking. Our exoskeleton has several limitations, especially for gait assistance in specific populations. Reducing the weight and the design of the exoskeleton in accordance to recent exoskeletons [1,3] could reduce the penalty of wearing the exoskeleton from 10% to less than 3%, even for autonomous devices. This suggests that reductions of more than 10% versus walking with normal shoes may be possible in healthy and physically active elderly by improvements in design of the exoskeleton only. Also, one subject was not able to walk comfortably with the exoskeleton (Electronic Supplementary material) due to knee flexion during stance, which perturbed exoskeleton assistance. This highlights the drawback of using a single assistance pattern that is not directly related to the user ‘s gait characteristics. For populations where individual differences are bigger, it will be important to gradually adapt exoskeleton assistance to the needs of each subject, for example by using myoelectric controllers [30]. On average, all perception scores were better and metabolic cost was lower in the second powered condition compared to the first powered condition, suggesting that habituation was not yet complete after the first powered condition. Longer habituation could potentially lead to bigger reductions in metabolic cost of walking. Since the good fitness and the high physical activity of our subjects might have influenced our results, future research with exoskeletons in elderly or patient populations could include physical activity and physical fitness as possible determinants for the effect of exoskeleton assistance. Also, a true comparison between exoskeleton walking in young adults and in elderly could further reveal differences and limitations for assistance in elderly. In conclusion, healthy and physically active elderly were able to walk with an ankle-foot exoskeleton that assisted plantarflexion during the push-off. This caused a reduction in metabolic cost versus powered-off exoskeleton walking. Although no statistically significant difference was found between powered exoskeleton walking and normal walking, improvements in design and more exoskeleton power should result in a reduction versus normal walking. As our subjects had good physical capabilities and were very physically active, it is hard to generalize our results to weaker elderly or other patient populations. Nevertheless, our results in healthy and physically active elderly are promising for future applications for exoskeletons as a tool to improve walking capacity in specific populations. Conflict of interest None. Acknowledgements The authors wish to thank Aqtor! for constructing the exoskeleton and Ing. Spiessens D. for the technical support. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j. gaitpost.2016.11.040. References [1] S.H. Collins, M.B. Wiggin, G.S. Sawicki, Reducing the energy cost of human walking using an unpowered exoskeleton, Nature 522 (2015) 212–215, doi: http://dx.doi.org/10.1038/nature14288.
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