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Haptic rehabilitation exercises performance evaluation using automated inference systems

机译:使用自动推理系统进行触觉康复锻炼表现评估

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Haptics and virtual environments offer the opportunity to improve the traditional methods of stroke rehabilitation. Traditionally, a therapist has to subjectively evaluate the patient's performance. This paper aims to introduce an automated inference system that utilises haptic data to quantise the patient's performance. Two systems were implemented: a Fuzzy Inference System (FIS) and an Adaptive Neuro-Fuzzy Inference System (ANFIS). The two systems were validated with sample input/output datasets. Testing with real subjects' data has led to the conclusion that the CyberForce system is incapable of providing normative data for evaluating the patient performance due to calibration and consistency issues.rnThis is an expanded version of a paper presented at the 3rd IEEE International Workshop on Medical Measurements and Applications, 9-10 May 2008, Ottawa, ON, Canada.
机译:触觉和虚拟环境为改善中风康复的传统方法提供了机会。传统上,治疗师必须主观评估患者的表现。本文旨在介绍一种利用触觉数据来量化患者表现的自动推理系统。实施了两个系统:模糊推理系统(FIS)和自适应神经模糊推理系统(ANFIS)。这两个系统已通过样本输入/输出数据集进行了验证。对真实受试者数据的测试得出的结论是,由于校准和一致性问题,Cyber​​Force系统无法提供用于评估患者表现的规范数据。这是在第三届IEEE国际医学研讨会上发表的论文的扩展版本。测量与应用,2008年5月9日至10日,加拿大安大略省渥太华。

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