Prosthesis rejection in acquired major upper-limb amputees: a population-based survey

Østlie, Kristin; Lesjø, Ingrid Marie; Franklin, Rosemary Joy; Garfelt, Beate; Skjeldal, Ola H.; Magnus, Per

doi:10.3109/17483107.2011.635405

Cited by 198 publications

(150 citation statements)

References 36 publications

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“…Supportive of this view, a review of the English language literature over a 25-year period observed that, while technology had improved, prosthetic limb rejection rates have not been decreasing, with 35 % of paediatric and 23 % of adult amputee populations discontinuing use of their prosthetic limb [49]. In a separate study, 13.4 % of Norwegian major upper limb amputees discontinued use of their prosthesis mainly due to poor prosthetic comfort, function and control [50].…”

Section: Pattern Recognition Controlmentioning

confidence: 99%

Prosthetic Myoelectric Control Strategies: A Clinical Perspective

et al. 2014

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Control algorithms for upper limb myoelectric prostheses have been in development since the mid-1940s. Despite advances in computing power and in the performance of these algorithms, clinically available prostheses are still based on the earliest control strategies. The aim of this review paper is to detail the development, advantages and disadvantages of prosthetic control systems and to highlight areas that are current barriers for the transition from laboratory to clinical practice. Current surgical strategies and future research directions to achieve multifunctional control will also be discussed. The findings from this review suggest that regression algorithms may offer an alternative feed-forward approach to direct and pattern recognition control, while virtual rehabilitation environments and tactile feedback could improve the overall prosthetic control.

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Section: Pattern Recognition Controlmentioning

confidence: 99%

Prosthetic Myoelectric Control Strategies: A Clinical Perspective

et al. 2014

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“…However, the actual impact of these technologies on patients' lives has been documented in only two case reports [10][11]. The question remains whether advanced devices may be more suited for some people with amputation and less for others based on underlying patient characteristics [12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Impact of Michelangelo prosthetic hand: Findings from a crossover longitudinal study

et al. 2015

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Abstract-This work explores the functional and psychosocial impact of the multigrip Michelangelo (M) prosthetic hand. Transradial myoelectric prosthesis users (6 men, median age: 47 y) participated in a crossover longitudinal study. A multifactorial assessment protocol was applied before the application of M and after 3 mo (functional assessment) and 6 mo (psychosocial assessment) of home use. Functional assessment included both practical tests (i.e., Southampton Hand Assessment Procedure [SHAP], Box and Blocks Test [BBT], and Minnesota Manual Dexterity Test [MMDT]) and self-report functional scales. Psychosocial assessment consisted of a clinical interview and a battery of self-report questionnaires concerning current anxious-depressive symptoms and healthrelated quality of life, body image concerns, adjustment and satisfaction with prosthesis, social support, coping style, and personality. Increased manual dexterity was observed after 3 mo based on improvements in the SHAP, BBT, and MMDT. Two important themes emerged from the clinical interviews at the 6 mo follow-up: (1) the enhanced functionality and (2) the "like a real hand" aspect of the M, which further increased prosthesis integration to the Self. A few patients expressed concerns about M dimension, noise, and weight. The M appeared to restore hand function and natural appearance. The present findings provide preliminary evidence, and additional studies are needed.

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“…HE human hand and arm are essential for a person to perform many daily life activities, including communication and interaction [1]. The loss of hand and wrist function after upper-limb amputation leads to significant disability [2].…”

Section: Introductionmentioning

confidence: 99%

Protocol for site selection and movement assessment for the myoelectric control of a multi-functional upper-limb prosthesis

Al-Timemy

Escudero

Bugmann

et al. 2013

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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Although there have been many advances in electromyography (EMG) signal processing and pattern recognition (PR) for the control of multi-functional upper-limb prostheses, some the outstanding problems need to be solved before practical PR-based prostheses can be put into service. Some of these are the lack of training and deployment protocols and the provision of the tools required. Therefore, we present a preliminary procedure to personalize the prosthesis deployment. In the first step, we record the demographic information of each individual amputee person and their background. In the second step of the protocol, the EMG signals are acquired. PR algorithms and parameters will be chosen in the 3(rd) step of the protocol. In the 4(th) step, the best number of EMG sensors to achieve the maximal performance with a full set of gestures is identified. The final step involves finding the best set of movements that the amputee person can produce with an accuracy > 95% as well as identifying the movements with the worst performance, which would require further training. This proposed approach is validated with 2 transradial amputees.

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Prosthesis rejection in acquired major upper-limb amputees: a population-based survey

Cited by 198 publications

References 36 publications

Prosthetic Myoelectric Control Strategies: A Clinical Perspective

Prosthetic Myoelectric Control Strategies: A Clinical Perspective

Impact of Michelangelo prosthetic hand: Findings from a crossover longitudinal study

Protocol for site selection and movement assessment for the myoelectric control of a multi-functional upper-limb prosthesis

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