A Measurement System for Hand Rehabilitation

Abstract

The emergence of some technological systems and smart devices that realize home-based or tele rehabilitation has exposed alternative delivery forms to promote patients’ hand recovery from common physiological conditions. However, due to the motion difficulty of most patients with an impaired hand, extra effort should be made to effectively stimulate their engagement without compromising the clinical outcomes.

The discussion about home-based medical equipment in both the market and academic realms indicates that a good recovery outcome of a home-based rehabilitation device seems to be closely related to the ease of use. The purpose of the research presented in this thesis is to investigate the feasibility of home-based hand rehabilitation with emphasis on ease of use. Towards this target, measurement techniques compatible with the overall aim are explored and selected. The framework of the measuring system is based on a MGC3030 capacitive sensing microcontroller, which allows the noncontact form of measurement of small fingers movements and potentially the thumb. This thesis reports the following parts to improve the stability and accuracy of the targeted measuring techniques:

• A Finite Element Method simulation based on the MGC3030 electrode stack-up design was carried out to guide the practical design of the electrodes. The original simulation model and the modified design with extra ground electrodes placed in between each pair of receive electrodes were compared and analysed.

• Algorithm compensation introduced nonlinear fitted equations to describe the inherent relationship between distance of finger motion and voltage signals. The signals were detected both in the receive electrode underneath the moving finger and the neighbouring ones, in an electrical field generated by an electrode layer stack-up design based on MGC3030 of two fingers’ motion (index finger together with the middle finger).
• A validation experiments was conducted to evaluate the prediction model on multi-finger noncontact measuring under laboratory conditions. Twenty-three healthy subjects with normal hand and finger functions participated. An independent near field distance measurement was developed and compared to the output from an optical sensor.

More information

Identifiers

ORCID for Nan Hu: orcid.org/0000-0002-8436-3575

ORCID for Nicholas Harris: orcid.org/0000-0003-4122-2219

ORCID for Neil White: orcid.org/0000-0003-1532-6452

Catalogue record

Export record