A deep learning wearable-based solution for continuous at-home monitoring of upper limb goal-directed movements.
A deep learning wearable-based solution for continuous at-home monitoring of upper limb goal-directed movements.
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DOI：
10.3389/fneur.2023.1295132
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发表时间：
2023
影响因子：
3.4
通讯作者：
Vaziri A
中科院分区：
文献类型：
--
作者：
Nunes AS;Yildiz Potter İ;Mishra RK;Bonato P;Vaziri A
监测上肢功能对于跟踪进展、评估治疗效果和识别潜在问题或并发症至关重要。手部目标导向运动（GDM）是日常生活的一个重要方面，反映了手部运动轨迹朝向特定目标位置的计划运动命令。先前的研究表明，GDM任务可以检测神经退行性疾病中上肢功能的早期变化，并可用于跟踪疾病随时间的进展。在这项研究中，我们使用了来自中风幸存者参与者和日常生活活动控制的加速度计数据，以开发一种自动化深度学习方法来检测GDM。从窗口数据检测GDM或非GDM的模型性能达到AUC 0.9，准确度0.83，灵敏度0.81，特异性0.84和F1 0.82。我们进一步验证了从GDM期提取特征检测GDM的实用性，并使用这些特征来分类测量值是从卒中幸存者还是对照参与者收集的，并预测卒中幸存者的Fugl-Meyer评估评分。这项研究提出了一个有前途的和可靠的工具，监测上肢功能在现实世界中的设置，并评估生物标志物与上肢健康的神经，神经肌肉和肌肉疾病。
Monitoring upper limb function is crucial for tracking progress, assessing treatment effectiveness, and identifying potential problems or complications. Hand goal-directed movements (GDMs) are a crucial aspect of daily life, reflecting planned motor commands with hand trajectories towards specific target locations. Previous studies have shown that GDM tasks can detect early changes in upper limb function in neurodegenerative diseases and can be used to track disease progression over time. In this study, we used accelerometer data from stroke survivor participants and controls doing activities of daily living to develop an automated deep learning approach to detect GDMs. The model performance for detecting GDM or non-GDM from windowed data achieved an AUC of 0.9, accuracy 0.83, sensitivity 0.81, specificity 0.84 and F1 0.82. We further validated the utility of detecting GDM by extracting features from GDM periods and using these features to classify whether the measurements are collected from a stroke survivor or a control participant, and to predict the Fugl-Meyer assessment score from stroke survivors. This study presents a promising and reliable tool for monitoring upper limb function in a real-world setting, and assessing biomarkers related to upper limb health in neurological, neuromuscular and muscles disorders.
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DOI：
10.3390/ijerph18041634
发表时间：
2021-02-09
影响因子：
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作者：
Chen PW;Baune NA;Zwir I;Wang J;Swamidass V;Wong AWK
通讯作者：
Wong AWK
影响因子：
2.4
作者：
Fauvel, Kevin;Lin, Tao;Termier, Alexandre
通讯作者：
Termier, Alexandre
影响因子：
3.9
作者：
Miao, Sheng;Shen, Chen;Lv, Zhihan
通讯作者：
Lv, Zhihan
影响因子：
4.6
作者：
Neishabouri, Ali;Nguyen, Joe;Samuelsson, John;Guthrie, Tyler;Biggs, Matt;Wyatt, Jeremy;Cross, Doug;Karas, Marta;Migueles, Jairo H.;Khan, Sheraz;Guo, Christine C.
通讯作者：
Guo, Christine C.
DOI：
10.1249/mss.0b013e3182351913
发表时间：
2012-04-01
期刊：
MEDICINE AND SCIENCE IN SPORTS AND EXERCISE
影响因子：
--
作者：
Feito, Yuri;Bassett, David R.;Thompson, Dixie L.
通讯作者：
Thompson, Dixie L.