Quantitative Measurement of Resistance to Passive Joint Motion in Chronic Stroke Survivors

Ewoldt, Jourdan; Raghavan, Preeti; Suresh, Nina L.

doi:10.1007/978-3-030-96900-4_4

Cited by 1 publication

(1 citation statement)

References 42 publications

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“…Mechanical limitations can be caused by atrophy of the extensor muscles, contracture of the flexor muscles, increased passive stiffness of the muscle tissue, or the shortening of muscle fibers. Neurophysiological disorders can result from flexor muscle spasticity, a weakness of the extensor muscles, or excessive contraction of the extensor and flexor muscles [49][50][51][52][53][54]. Robotic rehabilitation can lead to the alleviation of the occurrence of spasticity in the wrist joint [55].…”

Section: Introductionmentioning

confidence: 99%

Objectivizing Measures of Post-Stroke Hand Rehabilitation through Multi-Disciplinary Scales

Marek,

Redlicka,

Miller

et al. 2023

JCM

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There is a wide variety of tools and measures for rehabilitation outcomes in post-stroke patients with impairments in the upper limb and hand, such as paralysis, paresis, flaccidity, and spasticity. However, there is a lack of general recommendations for selecting the most appropriate scales, tests, and instruments to objectively evaluate therapy outcomes. Reviews on upper limb and hand measurements reveal that clinicians’ choices of tools and methods are highly varied. Some clinicians and medical teams continue to employ non-standard and unverified metrics in their research and measurements. This review article aims to identify the key parameters, assessed by outcome measures and instruments, that play a crucial role in upper limb and hand rehabilitation for post-stroke patients, specifically focusing on the recovery of hand function. The review seeks to assist researchers and medical teams in selecting appropriate outcome measures when evaluating post-stroke patients. We analyze the measured factors and skills found in these outcome measures and highlight useful tools that diversify assessments and enhance result objectivity through graphical representation. The paper also describes trends and new possibilities in hand outcome measures. Clinicians frequently use proven devices, such as EMG, goniometers, and hand dynamometers. Still, there is a growing trend towards incorporating technologies, such as pose and position estimation, using artificial intelligence, or custom hand grip measurement devices. Researchers are increasingly adopting scales previously successful in orthopedic and surgical patients, recognizing their potential for objectivizing outcomes in neurological patients with post-stroke hand complications. The review included only adults over the age of 18. Outcome measures were tested for usefulness in the rehabilitation of stroke patients.

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