@techreport{oai:ipsj.ixsq.nii.ac.jp:00216869,
 author = {上野, 拓海 and 関, 弘和 and Takumi, Ueno and Hirokazu, Seki},
 issue = {23},
 month = {Mar},
 note = {本研究では手指に痙縮の症状を持つ人を対象にした車椅子のハンドリム把持動作補助システムの開発を行った．装着型の把持動作補助装置を開発し，これを前腕部の筋電位信号に基づき制御することで車椅子の操作を実現した．筋電位の解析にはサポートベクターマシンを使用し，前腕の位置や姿勢に依らず高精度な把持動作判別が可能であることを示した．また実際の車椅子による直進や旋回等の操作性検証実験を実施し，提案システム の有効性を確認した．, In this study, we developed a wheelchair Handrim grasping assist system for people with spasticity in the fingers. We developed a wearable grasping assist device and controlled it based on EMG signals in the forearm to operate the wheelchair. SVM (Support Vector Machine) was used to analyze the EMG signals, and it was shown that the system could discriminate the grasping motion with high accuracy regardless of the position and posture of the forearm. The effectiveness of the proposed system was confirmed by conducting operability verification experiments such as straight driving and turning using an power-assisted wheelchair.},
 title = {車椅子使用者のためのハンドリム把持動作補助システムの開発},
 year = {2022}
}