A kinematic and kinetic dataset of 18 above-knee amputees walking at various speeds

Hood, Sarah; Ishmael, Marshall K.; Gunnell, Andrew; Foreman, K. Bo; Lenzi, Tommaso

doi:10.1038/s41597-020-0494-7

Cited by 42 publications

(52 citation statements)

References 34 publications

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“…The data collection protocol has been carefully documented in Hood et al (2020) (35), and data has been shared on Springer Nature, scientific data. The present study examined unilateral amputees walking on the treadmill who comfortably walked at or above 0.8 m/s were classified as full community ambulators (K3) (35). Seven male and two female transfemoral amputees (39.56±12.5 years old) participated after providing institutional-approved informed consent.…”

Section: Experimental Protocol and Data Collectionmentioning

confidence: 99%

Is there a Trade-off between Economy and Task Goal Variability in Transfemoral Amputee Gait?

Lee

Fylstra

Liu

et al. 2021

Preprint

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Background: Energy cost minimization has been widely accepted to regulate gait. Optimization principles have been frequently used to explain how individuals adapt their gait pattern. However, there have been rare attempts to account for the role of variability in this optimization process. Motor redundancy can enable individuals to perform tasks reliably while achieving energy optimization. However, we do not know how the goal-irrelevant and goal-relevant variability is regulated.. In this study, we investigated how unilateral transfemoral amputees regulate step and stride variability based on the task to achieve energy economy. Methods: Nine individuals with unilateral transfemoral amputation walked on a treadmill at speeds of 0.6,0.8,1.0,1.2 and 1.4 m/s using their prescribed passive prostheses. We calculated the step-to-step and stride-to-stride variability and applied goal equivalent manifold (GEM) based control to decompose goal-relevant and goal-irrelevant manifold. To quantify the energy economy, the energy recovery rate (R) was calculated based on potential energy and kinetic energy. Comparisons were made between GEM variabilities and commonly used standard deviation measurements. A linear regression model was used to investigate the trade-off between R and GEM variabilities. Results: Our analysis shows greater variability along the goal-relevant manifold compared to the goal-irrelevant manifold (p<.001). Moreover, our analysis shows lower energy recovery rate for amputee gait compared to nonamputee gait (at least 20% less at faster walking speed). We found a negative relationship between energy recovery rate and goal-irrelevant variability. Compared to the standard deviation measurements, the variability decomposed using GEM reflected the preferred walking speed and the limitation of the passive prosthetic device.Conclusion: Individuals with amputation cleverly leverage task redundancy, regulating step and stride variability to the goal equivalent manifold (GEM). This result suggests that task redundancy enables unilateral amputees to benefit from motor variability in terms of energy economy. The differences observed between prosthetic step and intact step support the development of prosthetic leg capable of enhancing positive work during the double support phase and of powered prosthesis controllers that allow for variability along the task space while minimizing variability that interferes with the task goal. This study provides a different perspective on amputee gait analysis and challenge the field to think differently about the role of variability.

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Section: Experimental Protocol and Data Collectionmentioning

confidence: 99%

Is there a Trade-off between Economy and Task Goal Variability in Transfemoral Amputee Gait?

Lee

Fylstra

Liu

et al. 2021

Preprint

Self Cite

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“…The rectification actions, i.e., the socket shape adjustments for improving fitness, are dictated by a theoretical framework, proposed by Radcliffe and other pioneers [ 1 , 4 ], based on classic engineering mechanics principles and clinical observations [ 5 ]. The lack of quantification is a principal factor restricting the levels of understanding and knowledge in prosthetic biomechanics [ 6 , 7 , 8 , 9 ]. The qualitative approach does not provide detailed knowledge of the interface loading and requires very strong clinical experience to pick up the subtle indicators of poor fitness [ 7 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

A Sensor-Based Decision Support System for Transfemoral Socket Rectification

Karamousadakis

Porichis

Ottikkutti

et al. 2021

Sensors

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A decision support system (DSS) was developed that outputs suggestions for socket-rectification actions to the prosthetist, aiming at improving the fitness of transfemoral prosthetic socket design and reducing the time needed for the final socket design. For this purpose, the DSS employs a fuzzy-logic inference engine (IE) which combines a set of rectification rules with pressure measurements generated by sensors embedded in the socket, for deciding the rectification actions. The latter is then processed by an algorithm that receives, manipulates and modifies a 3D digital socket model as a triangle mesh formatted inside an STL file. The DSS results were validated and tested in an FEA simulation environment, by simulating and comparing the donning process among a good-fitting socket, a loose socket (poor-fit) and several rectified sockets produced by the proposed DSS. The simulation results indicate that volume reduction improves the pressure distribution over the stump. However, as the intensity of socket rectification increases, i.e., as volume reduction increases, high pressures appear in other parts of the socket which generate discomfort. Therefore, a trade-off is required between the amount of rectification and the balance of the pressure distributions experienced at the stump.

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“…al. [23] is employed for this purpose containing optoelectronic and force plate data for transfemoral amputees.…”

Section: Introductionmentioning

confidence: 99%

Assessing the validity of dual-minima algorithm for heel-strike and toe-off prediction for the amputee population

Aftab

2021

Preprint

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Assessment of gait deficits relies on accurate gait segmentation based on the key gait events of heel strike (HS) and toe-off (TO). Kinematics-based estimation of gait events has shown promise in this regard especially using the leg velocity signal and gyroscopic sensors. However, its validation for the amputee population is not established in the literature. The goal of this study is to assess the accuracy of lower-leg angular velocity signal in determining the TO and HS instants for the amputee population. An open data set containing marker data of 10 subjects with unilateral transfemoral amputation during treadmill walking was used. A rule-based dual-minima algorithm was developed to detect the landmarks in the shank velocity signal indicating TO and HS events. The predictions were compared against the force platform data for 2595 walking cycles from 239 walking trials. Results showed considerable accuracy for the HS with a median error of -1ms. The TO prediction error was larger with the median ranging from 35-84ms. The algorithm consistently predicted the TO earlier than the actual event. Significant differences were found between the prediction accuracy for the sound and prosthetic legs. The prediction accuracy was also affected by the subjects' mobility level (K-level) but was largely unaffected by gait speed. In conclusion, the leg velocity profile during walking can predict the heel-strike and toe-off events for the transfemoral amputee population with varying degrees of accuracy depending upon the leg side and amputee's functional ability level.

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A kinematic and kinetic dataset of 18 above-knee amputees walking at various speeds

Cited by 42 publications

References 34 publications

Is there a Trade-off between Economy and Task Goal Variability in Transfemoral Amputee Gait?

Is there a Trade-off between Economy and Task Goal Variability in Transfemoral Amputee Gait?

A Sensor-Based Decision Support System for Transfemoral Socket Rectification

Assessing the validity of dual-minima algorithm for heel-strike and toe-off prediction for the amputee population

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