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7b.044.SBU - Human Behavior from Insole Sensor Data

Project - Summary

With Zeblok insole sensor, we can collect insole data from subjects. However, insole data can only provide us signals from the shoe and from these signals it is hard to tell what is happening to the subjects. In order to visualize the human behaviors that best correspond with insole sensor data, we use machine learning techniques to learn a mapping between the insole data and the full skeleton data. After learning such a mapping, we can predict other body motions of the subject that can be useful for diagnosis and for providing better healthcare.

Project - Team

Team Member Role Email Phone Number Academic Site/IAB
Arie E. Kaufman PI (631) 632-8428 Stony Brook University
Dimitris Samaras Co-PI (631) 632-8464 Stony Brook University
Huidong Liu Student Not Available (631) 632-8460 Stony Brook University
Salman Mahmood Student Not Available Not Available Stony Brook University
Mouli Narayanan Project Mentor Not Available Zeblok
Funded by: Zeblok

Project - Deliverables

1 Record human skeleton data using Kinect
2 Synchronize between insole data and skeleton data
3 Implement LSTM to learn mapping between insole data and skeleton data
4 Visualize skeleton data

Project - Documents

FilenameFilesizeLast modified
7b.044.sbu_2018_fall_meeting_poster.pptx112.7 KiB2019/08/13 15:09
7b.044.sbu_confluence_project_page.pdf168.9 KiB2019/08/13 15:09
7b.044.sbu_mid-year_report.docx237.3 KiB2019/08/13 15:09
projects/year7/7b.044.sbu.txt · Last modified: 2021/06/02 17:27 by sally.johnson