Use of assistive technology to assess distal motor function in subjects with neuromuscular disease.

PLOS digital health Pub Date : 2025-01-13 eCollection Date: 2025-01-01 DOI:10.1371/journal.pdig.0000534
Dominique Vincent-Genod, Sylvain Roche, Aurélie Barrière, Capucine de Lattre, Marie Tinat, Eelke Venema, Emmeline Lagrange, Adriana Gomes Lisboa de Souza, Guillaume Thomann, Justine Coton, Vincent Gautheron, Léonard Féasson, Pascal Rippert, Carole Vuillerot
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Abstract

Among the 32 items of the Motor Function Measure scale, 3 concern the assessment of hand function on a paper-based support. Their characteristics make it possible to envisage the use of a tablet instead of the original paper-based support for their completion. This would then make it possible to automate the score to reduce intra- and inter-individual variability. The main objective of the present study was to validate the digital completion of items 18, 19, and 22 by measuring the agreement of the scores obtained using a digital tablet with those obtained using the original paper-based support in children and adults with various neuromuscular diseases (NMD). The secondary objective is to calibrate an algorithm for the automatic items scoring.

Design: Prospective, multicentre, non-interventional study.

Methods: Ninety-eight subjects aged 5 to 60 years with a confirmed NMD completed MFM items 18, 19, and 22 both on a paper support and a digital tablet.

Results: The median age of included subjects was 16.2 years. Agreement between scores as assessed using the weighted Kappa coefficient was almost perfect for the scores of items 18 and 22 (K = 0.93, and 0.95, respectively) and substantial for item 19 (K = 0.70). In all cases of disagreement, the difference was of 1 point. The most frequent disagreement concerned item 19; mainly in the direction of a scoring of 1 point less on the tablet. An automatic analysis algorithm was tested on 82 recordings to suggest improvements.

Conclusion: The switch from original paper-based support to the tablet results in minimal and acceptable differences, and maintains a valid and reproducible measure of the 3 items. The developed algorithm for automatic scoring appears feasible with the perspective to include them in a digital application that will make it easier to monitor patients.

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使用辅助技术评估神经肌肉疾病患者远端运动功能。
在运动功能测量量表的32个项目中,有3个涉及对纸质支撑的手功能的评估。它们的特点使人们可以设想使用平板电脑而不是原始的基于纸张的支持来完成它们。这将使自动评分成为可能,以减少个体内部和个体之间的差异。本研究的主要目的是通过测量在患有各种神经肌肉疾病(NMD)的儿童和成人中使用数字平板电脑获得的分数与使用原始纸质支持获得的分数的一致性,来验证项目18、19和22的数字完成情况。第二个目标是校准自动项目评分的算法。设计:前瞻性、多中心、非干预性研究。方法:98名5 ~ 60岁确诊NMD的受试者分别使用纸质支持器和数字平板电脑完成MFM项目18、19、22。结果:纳入受试者的中位年龄为16.2岁。使用加权Kappa系数评估的分数之间的一致性对于项目18和22的分数(K分别= 0.93和0.95)几乎是完美的,对于项目19 (K = 0.70)来说是实质性的。在所有不同意的情况下,差异为1分。最常见的分歧涉及项目19;主要是在一个方向上得分少1分的平板电脑上。一种自动分析算法对82个录音进行了测试,以提出改进建议。结论:从原来的纸质支持切换到片剂的结果是最小的和可接受的差异,并保持了有效和可重复的3项测量。从将自动评分纳入数字应用程序的角度来看,开发的自动评分算法似乎是可行的,这将使监测患者变得更容易。
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