Sensoria, a textile sensor company, has launched a new app, called Sensoria Walk, which helps users track their activity during rehabilitation after a stroke or post-surgery. The app aims to speed up patient recovery time.
Sensoria first announced the Sensoria Walk app at CES 2016.
“This solution is designed specifically for people in particular circumstances where a traditional wrist-based activity tracking device may not be providing the necessary accurate level of activity monitoring that you might need,” Sensoria Director of Marketing and Business Development Alick Law explained in a video a few months ago. “These scenarios include people with shuffling gait, people who are using walkers, or people with short stride length, for example.”
Sensoria Walk syncs with Sensoria’s Smart Socks, which launched commercially in May 2015, and tracks a user’s progress history, goals, steps, distance, and total activity time. The socks track activity using an anklet attached to the sock, which communicates with the app via Bluetooth.
“According to a 2013 research study published by the Mayo Clinic, there is a direct correlation between activity and faster recovery time,” Sensoria Cofounder and CEO Davide Vigano said when the app was announced in January. “However, most wrist worn wearable devices cannot accurately detect the activity of people with limited mobility, such as elderly patients or patients recovering from surgery or using a walker. Sensoria Walk aims to deliver a more accurate tool for patients and caregivers to track and evaluate their recovery progress.”
This isn’t the first healthcare-related move Sensoria has made recently.
In October 2015, Sensoria announced it had partnered with New York medical device company Orthotics Holdings Incorporated (OHI) to incorporate the textile sensors it uses in its smart socks into the Moore Balance Brace, an orthotic brace from OHI. The new product is called the Smart Moore Balance Brace. The brace will track not just motion, but things like gait, cadence, and stride length that physical therapists can analyze to predict falls and track recovery.
