NDLI: Inviz: Low-power personalized gesture recognition using wearable textile capacitive sensor arrays

Content Provider	IEEE Xplore Digital Library
Author	Singh, G. Nelson, A. Robucci, R. Patel, C. Banerjee, N.
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Sci. & Electr. Eng., Univ. of Maryland, Baltimore, MD, USA (Singh, G.; Nelson, A.; Robucci, R.; Patel, C.; Banerjee, N.)
Abstract	Home automation and environmental control is a key ingredient of smart homes. While systems for home automation and control exist, there are few systems that interact with individuals suffering from paralysis, paresis, weakness and limited range of motion that are common sequels resulting from severe injuries such as stroke, brain injury, spinal cord injury and many chronic (guillian barre syndrome) and degenerative (amyotrophic lateral sclerosis) conditions. To address this problem, we present the design, implementation, and evaluation of Inviz, a low-cost gesture recognition system for paralysis patients that uses flexible textile-based capacitive sensor arrays for movement detection. The design of Inviz presents two novel research contributions. First, the system uses flexible textile-based capacitive arrays as proximity sensors that are minimally obtrusive and can be built into clothing for gesture and movement detection in patients with limited body motion. The proximity sensing obviates the need for touch-based gesture recognition that can cause skin abrasion in paralysis patients, and the array of capacitive sensors help provide better spatial resolution and noise cancellation. Second, Inviz uses a low-power hierarchical signal processing algorithm that breaks down computation into multiple low and high power tiers. The tiered approach provides maximal vigilance at minimal energy consumption. We have designed and implemented a fully functional prototype of Inviz and we evaluate it in the context of an end-to-end home automation system and show that it achieves high accuracy while maintaining low latency and low energy consumption.
Starting Page	198
Ending Page	206
File Size	1660528
Page Count	9
File Format	PDF
ISBN	9781479980338
DOI	10.1109/PERCOM.2015.7146529
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-03-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Capacitive sensors Sensor arrays Gesture recognition Capacitance Capacitors Signal processing algorithms
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Demo abstract: Inviz: Low-power personalized gesture recognition using wearable textile capacitive sensor arrays

Inviz: Low-power Personalized Gesture Recognition using Wearable Textile Capacitive Sensor Arrays

Demo Abstract: Inviz: Low-power Personalized Gesture Recognition Using Wearable Textile Capacitive Sensor Arrays

Adaptive and Personalized Gesture Recognition Using Textile Capacitive Sensor Arrays

A textile based capacitive pressure sensor

Signal conditioning for capacitive sensors with field programmable analog arrays

An accurate smart capacitive angular-position sensor with a full circle range

A simple and ultra-low power capacitive pressure micro-sensor sensing system design

Capacitive fingerprint sensor chip for automatic matching

Inviz: Low-power personalized gesture recognition using wearable textile capacitive sensor arrays

Similar Documents

Demo abstract: Inviz: Low-power personalized gesture recognition using wearable textile capacitive sensor arrays

Inviz: Low-power Personalized Gesture Recognition using Wearable Textile Capacitive Sensor Arrays

Demo Abstract: Inviz: Low-power Personalized Gesture Recognition Using Wearable Textile Capacitive Sensor Arrays

Adaptive and Personalized Gesture Recognition Using Textile Capacitive Sensor Arrays

A textile based capacitive pressure sensor

Signal conditioning for capacitive sensors with field programmable analog arrays

An accurate smart capacitive angular-position sensor with a full circle range

A simple and ultra-low power capacitive pressure micro-sensor sensing system design

Capacitive fingerprint sensor chip for automatic matching

Inviz: Low-power personalized gesture recognition using wearable textile capacitive sensor arrays