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Objective measures of human hands as individuals participate in everyday activities are needed in order to expand the dexterous use of the hand or to evaluate the hand functions in rehabilitation or skill training. Data gloves for measurements of finger movements are a promising tool for this purpose. The requirements for the data glove include easy and comfortable to wear and remove, durability, cost-effectiveness and measurement repeatability and reliability. SmartGlove is a wearable glove-based multi-finger motion capture device with a specific focus on the development of a new optical linear encoder (OLE) with novel sensing technology. The specially designed OLE has a compact size, light weight and low power consumption. SmartGlove adopts the innovative multi-location sensing principle. The basic working principle is to place multiple OLEs in series on different finger segments to capture the displacements of different detecting points using the same strip. The first prototype of SmartGlove which uses ten OLEs to capture the flexion/extension motion of the 14 finger joints is constructed based on the multi-point sensing method. A case study for the evaluation of SmartGlove using a standard protocol shows high repeatability and reliability in both the gripped and flat hand positions compared with another four evaluated data gloves using the same protocol. Conclusively, measuring outcomes in a portable manner can provide important information for the utilization and evaluation of the hands motion data.
Chen yi ting
Li Kang(NTU,Singapore) teacher :Chen I Ming(NTU,Singapore)