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Tom Chau

Researcher at University of Toronto

Publications -  303
Citations -  11981

Tom Chau is an academic researcher from University of Toronto. The author has contributed to research in topics: Brain–computer interface & Swallowing. The author has an hindex of 51, co-authored 292 publications receiving 10475 citations. Previous affiliations of Tom Chau include Holland Bloorview Kids Rehabilitation Hospital & National Telecommunications and Information Administration.

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Upper limb prosthesis use and abandonment: A survey of the last 25 years:

TL;DR: An analytical and comparative survey of upper limb prosthesis acceptance and abandonment as documented over the past 25 years is presented, detailing areas of consumer dissatisfaction and ongoing technological advancements.
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Short-Term Music Training Enhances Verbal Intelligence and Executive Function

TL;DR: The effects of two interactive computerized training programs developed for preschool children: one for music and one for visual art demonstrate that transfer of a high-level cognitive skill is possible in early childhood.
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Upper-limb prosthetics: critical factors in device abandonment.

TL;DR: Improved follow-up, repair, and information services, together with active involvement of clients in the selection of prostheses meeting their specific goals and needs, is recommended.
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Consumer design priorities for upper limb prosthetics

TL;DR: Lower cost ranked within the top five design priorities for adult wearers of all device types and life-like appearance is a priority for passive/cosmetic prostheses, while improved harness comfort, wrist movement, grip control and strength are required for body-powered devices.
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A review of analytical techniques for gait data. Part 1: fuzzy, statistical and fractal methods

Tom Chau
- 01 Feb 2001 - 
TL;DR: In this article, a critical survey of recent gait studies is presented, and the potential of these methods to strengthen the gait laboratory's analytical arsenal is reviewed. But, although initially promising, fuzzy and fractal analyses of gait data remain largely unknown and their full potential is yet to be realized.