SocialBit: protocol for a prospective observational study to validate a wearable social sensor for stroke survivors with diverse neurological abilities
Introduction Social isolation has been found to be a significant risk factor for health outcomes, on par with traditional risk factors. This isolation is characterised by reduced social interactions, which can be detected acoustically. To accomplish this, we created a machine learning algorithm call...
Saved in:
| Main Authors: | Matthias R Mehl, Ross Zafonte, Kelly White, Samuel Tate, Shrikanth Narayanan, Min Shin, Amar Dhand |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMJ Publishing Group
2023-08-01
|
| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/13/8/e076297.full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Wearable Sensors and Motion Analysis for Neurological Patient Support
by: Peter Dabnichki, et al.
Published: (2024-12-01) -
Multiple-Wearable-Sensor-Based Gait Classification and Analysis in Patients with Neurological Disorders
by: Wei-Chun Hsu, et al.
Published: (2018-10-01) -
Social Reintegration Experiences of Young Adult Cancer Survivors
by: Ji Seong Yi, et al.
Published: (2024-11-01) -
Development of a wearable activity tracker based on BBC micro:bit and its performance analysis for detecting bachata dance steps
by: Kemal Avci
Published: (2024-12-01) -
Qualitative study on the ability of neurological nurses to manage patients with indwelling gastrointestinal canal
by: Zezhou Wang, et al.
Published: (2024-12-01)