The influence of powered prostheses on user perspectives, metabolics, and activity: a randomized crossover trial

Jay Kim, Jeffrey Wensman, Natalie Colabianchi, Deanna H Gates, Jay Kim, Jeffrey Wensman, Natalie Colabianchi, Deanna H Gates

Abstract

Background: Powered prosthetic ankles provide battery-powered mechanical push-off, with the aim of reducing the metabolic demands of walking for people with transtibial amputations. The efficacy of powered ankles has been shown in active, high functioning individuals with transtibial amputation, but is less clear in other populations. Additionally, it is unclear how use of a powered prosthesis influences everyday physical activity and mobility.

Methods: Individuals with unilateral transtibial amputations participated in a randomized clinical trial comparing their prescribed, unpowered prosthesis and the BiOM powered prosthesis. Participants' metabolic costs and self-selected walking speeds were measured in the laboratory and daily step count, daily steps away from home, and walking speed were measured over two weeks of at-home prosthesis use. Participants also rated their perception of mobility and quality of life and provided free-form feedback. Dependent measures were compared between prostheses and the relationships between metabolic cost, perception of mobility, and characteristics of walking in daily life were explored using Pearson's correlations.

Results: Twelve people were randomly allocated to the powered prosthesis first (n = 7) or unpowered prosthesis first (n = 5) and ten completed the full study. There were no differences in metabolic costs (p = 0.585), daily step count (p = 0.995), walking speed in-lab (p = 0.145) and in daily life (p = 0.226), or perception of mobility between prostheses (p ≥ 0.058). Changes varied across participants, however. There were several medium-sized effects for device comparisons. With the powered prosthesis, participants had increased self-reported ambulation (g = 0.682) and decreased frustration (g = 0.506).

Conclusions: There were no universal benefits of the powered prosthesis on function in the lab or home environment. However, the effects were subject-specific, with some reporting preference for power and improved mobility, and some increasing their activity and decreasing their metabolic effort. Additionally, self-reported preferences did not often correlate with objective measures of function. This highlights the need for future clinical research to include both perception and objective measures to better inform prosthetic prescription.

Trial registration: https://ichgcp.net/clinical-trials-registry/NCT02828982" title="See in ClinicalTrials.gov">#NCT02828982. Registered 12 July 2016, https://ichgcp.net/clinical-trials-registry/NCT02828982.

Keywords: Accelerometer; Inertial measurement unit; Metabolic cost; Microprocessor ankle; Preference; Step count; Transtibial amputation; Walking speed.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Consort flow diagram illustrating recruitment, enrollment, exclusion, and analysis
Fig. 2
Fig. 2
a Daily step count using the unpowered (red) and powered (blue) prostheses. Dashed horizontal line represents the recommended 10,000 steps per day. b Daily step count away from home using the unpowered (red) and powered (blue) prostheses. Gray x’s and lines represent individual participant trends
Fig. 3
Fig. 3
a Self-selected walking speeds measured in the lab for participants using the unpowered (red) and powered (blue) prostheses. Gray x’s and lines represent individual participant trends. b Split violin plot of the probability density functions of walking speed distributions of walking strides taken in daily life. To visualize, raw distributions were smoothed using the ksdensity kernel smoothing function in MATLAB. Shared regions are averaged distributions and solid horizontal lines are the group means
Fig. 4
Fig. 4
Changes in participant responses for the Prosthesis Evaluation Questionnaire, Short Form-36 and Prosthesis Preference, by sub-scale. Significant differences (p g ≥ 0.5) are also indicated and bolded (†)
Fig. 5
Fig. 5
a Relationship between changes in prosthesis preference and changes in metabolic cost (ΔCOT). Dashed lines indicate the minimal detectable change in COT. b Relationship between changes in prosthesis preference and changes in daily step count. c Relationship between changes in prosthesis preference and changes in walking speed in daily life. Linear fits are shown for moderate correlations (r ≥ 0.6)
Fig. 6
Fig. 6
a Relationship between changes in metabolic cost (ΔCOT) and changes in daily step count. Data in the second quadrant (highlighted in green) indicate lower metabolic cost and greater step count with the powered prosthesis. b Relationships between changes in the PEQ ambulation sub-scale (left) and the SF-36 physical functioning sub-scale scores (right) and changes in daily step count.c Relationships between changes in the PEQ social burden sub-scale (left) and the SF-36 social functioning sub-scale scores (right) and changes in daily step count away from home. Data in the first quadrant (highlighted in green) indicate greater scores and greater step count with the powered prosthesis

References

    1. Waters RL, Mulroy S. The energy expenditure of normal and pathologic gait. Gait Posture. 1999;9(3):207–31. doi: 10.1016/S0966-6362(99)00009-0.
    1. Lin SJ, Winston KD, Mitchell J, Girlinghouse J, Crochet K. Physical activity, functional capacity, and step variability during walking in people with lower-limb amputation. Gait Posture. 2014;40(1):140–4. doi: 10.1016/j.gaitpost.2014.03.012.
    1. Stepien JM, Cavenett S, Taylor L, Crotty M. Activity levels among lower-limb amputees: self-report versus step activity monitor. Arch Phys Med Rehabil. 2007;88(7):896–900. doi: 10.1016/j.apmr.2007.03.016.
    1. Klute GK, Berge JS, Orendurff MS, Williams RM, Czerniecki JM. Prosthetic intervention effects on activity of lower-extremity amputees. Arch Phys Med Rehabil. 2006;87(5):717–22. doi: 10.1016/j.apmr.2006.02.007.
    1. Orendurff MS, Schoen JA, Bernatz GC, Segal AD, Klute GK. How humans walk: bout duration, steps per bout, and rest duration. J Rehabil Res Dev. 2008;45(7):1077–89. doi: 10.1682/JRRD.2007.11.0197.
    1. Pell J, Donnan P, Fowkes F, Ruckley C. Quality of life following lower limb amputation for peripheral arterial disease. Eur J Vasc Surg. 1993;7(4):448–51. doi: 10.1016/S0950-821X(05)80265-8.
    1. Haskell WL, Blair SN, Hill JO. Physical activity: health outcomes and importance for public health policy. Prevent Med. 2009;49(4):280–2. doi: 10.1016/j.ypmed.2009.05.002.
    1. Au SK, Weber J, Herr H. Powered ankle-foot prosthesis improves walking metabolic economy. Trans Rob. 2009;25(1):51–66. doi: 10.1109/TRO.2008.2008747.
    1. Herr HM, Grabowski AM. Bionic ankle-foot prosthesis normalizes walking gait for persons with leg amputation. Proc Biol Sci. 2012;279(1728):457–64.
    1. Russell Esposito E, Aldridge Whitehead JM, Wilken JM. Step-to-step transition work during level and inclined walking using passive and powered ankle-foot prostheses. Prosthet Orthot Int. 2016;40(3):311–9. doi: 10.1177/0309364614564021.
    1. Gardinier ES, Kelly BM, Wensman J, Gates DH. A controlled clinical trial of a clinically-tuned powered ankle prosthesis in people with transtibial amputation. Clin Rehabil. 2018;32(3):319–29. doi: 10.1177/0269215517723054.
    1. Montgomery JR, Grabowski AM. Use of a powered ankle-foot prosthesis reduces the metabolic cost of uphill walking and improves leg work symmetry in people with transtibial amputations. nJ R Soc Interface. 2018;15(145):20180442. doi: 10.1098/rsif.2018.0442.
    1. Gates DH, Aldridge JM, Wilken JM. Kinematic comparison of walking on uneven ground using powered and unpowered prostheses. Clin Biomech. 2013;28(4):467–72. doi: 10.1016/j.clinbiomech.2013.03.005.
    1. Ferris AE, Aldridge JM, Rabago CA, Wilken JM. Evaluation of a powered ankle-foot prosthetic system during walking. Arch Phys Med Rehabil. 2012;93(11):1911–8. doi: 10.1016/j.apmr.2012.06.009.
    1. Medicare C. HCFA Common Procedure Coding System (HCPCS) Springfield (VA): US Department of Commerce. National Technical Information Service. 2001.
    1. World Health Organization . International classification of functioning, disability and health: ICF. Geneva: World Health Organization; 2001.
    1. Chadwell A, Diment L, Mico-Amigo M, Morgado Ramirez DZ, Dickinson A, Granat M, Kenney L, Kheng S, Sobuh M, Ssekitoleko R, Worsley P. Technology for monitoring everyday prosthesis use: a systematic review. J Neuroeng Rehabil. 2020;17(1):93. doi: 10.1186/s12984-020-00711-4.
    1. Stamford B, Noble B. Metabolic cost and perception of effort during bicycle ergometer work performance. Med Sci Sports. 1974;6(4):226–31.
    1. Bowden MG, Behrman AL. Step activity monitor: accuracy and test-retest reliability in persons with incomplete spinal cord injury. J Rehabil Res Dev. 2007;44(3):355–62. doi: 10.1682/JRRD.2006.03.0033.
    1. Rebula JR, Ojeda LV, Adamczyk PG, Kuo AD. Measurement of foot placement and its variability with inertial sensors. Gait Posture. 2013;38(4):974–80. doi: 10.1016/j.gaitpost.2013.05.012.
    1. Gates DH, Scott SJ, Wilken JM, Dingwell JB. Frontal plane dynamic margins of stability in individuals with and without transtibial amputation walking on a loose rock surface. Gait Posture. 2013;38(4):570–5. doi: 10.1016/j.gaitpost.2013.01.024.
    1. Davidson A, Gardinier ES, Gates DH. Within and between-day reliability of energetic cost measures during treadmill walking. Cogent Eng. 2016;3(1251028):1–7.
    1. Legro MW, Reiber GD, Smith DG, del Aguila M, Larsen J, Boone D. Prosthesis evaluation questionnaire for persons with lower limb amputations: assessing prosthesis-related quality of life. Arch Phys Med Rehabil. 1998;79(8):931–8. doi: 10.1016/S0003-9993(98)90090-9.
    1. Brockway J. Derivation of formulae used to calculate energy expenditure in man. Human Nutr Clin Nutr. 1987;41(6):463–71.
    1. Donelan MJ, Kram R, Kuo AD. Mechanical and metabolic determinants of the preferred step width in human walking. Proc R Soc Lond B Biol Sci. 2001;268(1480):1985–1992. doi: 10.1098/rspb.2001.1761.
    1. Kim J, Colabianchi N, Wensman J, Gates DH. Wearable sensors quantify mobility in people with lower limb amputation during daily life. IEEE Trans Neural Sys Rehab Eng. 2020;28(6):1282–91. doi: 10.1109/TNSRE.2020.2990824.
    1. Theeven PJ, Hemmen B, Geers RP, Smeets RJ, Brink PR, Seelen HA. Influence of advanced prosthetic knee joints on perceived performance and everyday life activity level of low-functional persons with a transfemoral amputation or knee disarticulation. J Rehabil Med. 2012;44(5):454–61. doi: 10.2340/16501977-0969.
    1. Ojeda L, Borenstein J. Personal dead-reckoning system for GPS-denied environments. In: 2007 IEEE International Workshop on Safety, Security and Rescue Robotics. 2007:1–6.
    1. Rice JA. Mathematical statistics and data analysis. Boston: Cengage Learning; 2006.
    1. Durlak JA. How to select, calculate, and interpret effect sizes. J Pediatr Psychol. 2009;34(9):917–28. doi: 10.1093/jpepsy/jsp004.
    1. Cohen J. Statistical power analysis for the behavioral sciences. Academic press: Cambridge; 2013.
    1. Tudor-Locke C, Bassett DR., Jr How many steps/day are enough? Preliminary pedometer indices for public health. Sports Med. 2004;34(1):1–8. doi: 10.2165/00007256-200434010-00001.
    1. Wanamaker AB, Andridge RR, Chaudhari AM. When to biomechanically examine a lower-limb amputee:a systematic review of accommodation times. Prosthet Orthot Int. 2017;41(5):431–45. doi: 10.1177/0309364616682385.
    1. Wurdeman SR, Myers SA, Jacobsen AL, Stergiou N. Adaptation and prosthesis effects on stride-to-stride fluctuations in amputee gait. PLoS One. 2014;9(6):e100125. doi: 10.1371/journal.pone.0100125.
    1. Grabowski AM, Rifkin J, Kram R. K3 Promoter™ prosthetic foot reduces the metabolic cost of walking for unilateral transtibial amputees. JPO. 2010;22(2):113–20.
    1. Goldberg A, Schepens S. Measurement error and minimum detectable change in 4-meter gait speed in older adults. Aging Clin Exp Res. 2011;23(5–6):406–12. doi: 10.1007/BF03325236.

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