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. 2020 Oct;28(10):2265-2275.
doi: 10.1109/TNSRE.2020.3021691. Epub 2020 Sep 4.

User-Driven Functional Movement Training With a Wearable Hand Robot After Stroke

Sangwoo Park, Michaela Fraser, Lynne M Weber, Cassie Meeker, Lauri Bishop, Daniel Geller, Joel Stein, Matei Ciocarlie

User-Driven Functional Movement Training With a Wearable Hand Robot After Stroke

Sangwoo Park et al. IEEE Trans Neural Syst Rehabil Eng. 2020 Oct.

Abstract

We studied the performance of a robotic orthosis designed to assist the paretic hand after stroke. It is wearable and fully user-controlled, serving two possible roles: as a therapeutic tool that facilitates device-mediated hand exercises to recover neuromuscular function or as an assistive device for use in everyday activities to aid functional use of the hand. We present the clinical outcomes of a pilot study designed as a feasibility test for these hypotheses. 11 chronic stroke (>2 years) patients with moderate muscle tone (Modified Ashworth Scale ≤ 2 in upper extremity) engaged in a month-long training protocol using the orthosis. Individuals were evaluated using standardized outcome measures, both with and without orthosis assistance. Fugl-Meyer post intervention scores without robotic assistance showed improvement focused specifically at the distal joints of the upper limb, suggesting the use of the orthosis as a rehabilitative device for the hand. Action Research Arm Test scores post intervention with robotic assistance showed that the device may serve an assistive role in grasping tasks. These results highlight the potential for wearable and user-driven robotic hand orthoses to extend the use and training of the affected upper limb after stroke.

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Figures

Fig. 1.
Fig. 1.
Top : Exotendon device and EMG armband. Bottom : Functional movement training with a wearable hand orthosis.
Fig. 2.
Fig. 2.
Tendon routes for the thumb (left) and fingertip components (right).
Fig. 3.
Fig. 3.
EMG armband or SH, depending on the assigned group, sends biophysical data to a computer through bluetooth or microcontroller unit (MCU). In the computer, intent detection algorithm classifies the intention and generate a motor command. Then, the command is transmitted to the motor through the MCU.
Fig. 4.
Fig. 4.
Exotendon device with SH method.
Fig. 5.
Fig. 5.
Real world objects used for treatment.
Fig. 6.
Fig. 6.
FM(left) and ARAT(right) scores. Subject 5 dropped out due to a medical issue unrelated to the study.
See this image and copyright information in PMC

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