Non-contact temporalis muscle monitoring to detect eating in free-living using smart eyeglasses

Saphala, Addythia; Zhang, Rui; Thai, Trinh Nam; Amft, Oliver

doi:10.1109/bsn56160.2022.9928447

Cited by 1 publication

(1 citation statement)

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“…Another promising long-term solution could be the contact-free detection of the Temporalis muscle contraction by proximity sensors. This approach was already tested for dietary monitoring and eating event detection by Saphala et al [31,32] and Selamat et al [33] and could be adapted to our interface with little effort.…”

Section: Overall Systemmentioning

confidence: 99%

Design and Implementation of a Personalizable Alternative Mouse and Keyboard Interface for Individuals with Limited Upper Limb Mobility

Andreas

Six

Bliek

et al. 2022

MTI

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People with neuromuscular diseases often experience limited upper limb mobility, which makes the handling of standard computer mice and keyboards difficult. Due to the importance of computers in private and professional life, this work aims at implementing an alternative mouse and keyboard interface that will allow for their efficient use by people with a neuromuscular disease. Due to the strongly differing symptoms of these diseases, personalization on the hardware and software levels is the focus of our work. The presented mouse alternative is based on a spectacle frame with an integrated motion sensor for head tracking, which enables the control of the mouse cursor position; the keyboard alternative consists of ten keys, which are used to generate word suggestions for the user input. The interface was tested in a user study involving three participants without disabilities, which showed the general functionality of the system and potential room for improvement. With an average throughput of 1.56 bits per second achieved by the alternative mouse and typing speeds of 8.44 words per minute obtained using the alternative keyboard, the proposed interface could be a promising input device for people with limited upper limb mobility.

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Section: Overall Systemmentioning

confidence: 99%