Literature DB >> 30853689

Evaluation of Motor-Assisted Gloves (SEM Glove) for Patients with Functional Finger Disorders: A Clinical Pilot Study.

Ryuki Hashida1,2, Hiroo Matsuse1,2, Masafumi Bekki1,2, Masayuki Omoto1,2, Shimpei Morimoto3, Tomoko Hino1, Yuuji Harano1, Chikahiro Iwasa1, Kazuki Miyamoto1, Masakuni Haraguchi1, Takeshi Nago1,2, Naoto Shiba1,2.   

Abstract

The SEM Glove developed by Bioservo Technologies AB is a new device that increases grip and pinch force. The purpose of this study was to evaluate the effectiveness of the device on the grip and pinch strength of patients with functional disorders of the fingers. MATERIALS AND
METHOD: 30 hospitalized patients with upper limb functional disorder were enrolled. The assistance of the device for the grip and pinch strength of each subject were assessed by the difference between the measured values with and without the SEM Glove. The 95% confidence interval of the difference was calculated across the subjects, and statistical significance was defined as when the lower limit was a positive value (corresponding with a paired t-test at a significance level of 0.05). The odds ratio was calculated in the study of subject adaptation, with statistical significance set using Fisher's exact test at a significance level of 0.05.
RESULTS: Grip strength significantly decreased (worn-not worn difference (kg): mean = -3.7, CI95 (-5.4, -2.1)). Pinch strength (thumb - middle finger) significantly increased (worn-not worn difference (N): mean = -4.1, CI95 (1.6, 6.6)). Analysis of factors related to improvement in hand function when wearing the SEM Glove extracted manual muscle tests (MMTs) of the upper extremity 4 or higher. The odds ratio was 6.11.
CONCLUSIONS: Use of the SEM Glove improved the pinch strength of patients with functional disorders of the hands.

Entities:  

Keywords:  hand function; pinch strength; upper limb disorders

Mesh:

Year:  2019        PMID: 30853689     DOI: 10.2739/kurumemedj.MS652007

Source DB:  PubMed          Journal:  Kurume Med J        ISSN: 0023-5679


  1 in total

1.  Effective Multi-Mode Grasping Assistance Control of a Soft Hand Exoskeleton Using Force Myography.

Authors:  Muhammad Raza Ul Islam; Shaoping Bai
Journal:  Front Robot AI       Date:  2020-11-16
  1 in total

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