SBIR-STTR Award

New Wearable for Body Focused Repetitive Behavior Detection
Award last edited on: 3/3/2021

Sponsored Program
SBIR
Awarding Agency
NSF
Total Award Amount
$1,239,053
Award Phase
2
Solicitation Topic Code
DH
Principal Investigator
John Pritchard

Company Information

Habitaware Inc

7204 West 27th Street Suite 107
Minneapolis, MN 55426
   (712) 389-0381
   hello@habitaware.com>
   www.habitaware.com
Location: Single
Congr. District: 05
County: Hennepin

Phase I

Contract Number: 1914175
Start Date: 7/1/2019    Completed: 3/31/2020
Phase I year
2019
Phase I Amount
$224,795
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will result from providing an accurate real-time awareness solution for those who suffer from body-focused repetitive behaviors. Over 4% of Americans suffer from skin picking, hair pulling, and nail biting, the majority of whom resort to covering up the problem with makeup, gloves, wigs, and even tattoos due to treatment cost barriers and lack of effective tools to facilitate behavior change. While behavior therapy, and in particular habit reversal training, has shown efficacy, this method is traditionally burdened by unreliable journaling, a lack of access to treatment, and difficulty for patients to perform in real-time because of a lack of awareness. While real-time awareness devices do exist, there is room for improvement in detection accuracy. This project will examine feasibility of a novel sensor system within a wearable device that can significantly improve detection accuracy of BFRB-related behaviors. This Small Business Innovation Research Phase I project will develop and validate a novel wearable sensing system used to detect subtle movements associated with BFRBs that is suitable for large-scale manufacturing. We believe the proposed wearable system can improve the efficacy of leading behavior therapy methods. To accomplish these goals, early studies will focus on three main objectives. First, the team will investigate the best electrical and spatial configuration of the proposed sensors in a tightly controlled test setup. Second, the team will integrate the optimal configuration into a device suitable for testing and validate the integrity of the sensor output on individuals. Finally, the team will develop a proof-of-concept BFRB recognition algorithm under ideal, low-noise conditions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Phase II

Contract Number: 2026173
Start Date: 9/15/2020    Completed: 8/31/2022
Phase II year
2020
(last award dollars: 2021)
Phase II Amount
$1,014,258

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will help people who suffer from body-focused repetitive behaviors (BFRBs). Over 4% of Americans suffer from skin picking, hair pulling, and nail biting, the majority of whom resort to covering up the problem with makeup, gloves, wigs, and even tattoos due to treatment cost barriers and lack of effective tools to facilitate behavior change. While behavior therapy, and in particular habit reversal training, has shown efficacy, this method is traditionally burdened by unreliable journaling, a lack of access to treatment, and difficulty for patients to perform in real-time because of a lack of awareness. While real-time awareness devices do exist, there is room for improvement in detection accuracy. This project will integrate a novel sensor system into a wearable device that can lead to state-of-the-art detection accuracy of BFRB-related behaviors. This wearable sensor solution is the first of its kind, using the novel sensor to extract meaningful biomechanical information. This Small Business Innovation Research (SBIR) Phase II project will result in new behavior recognition algorithms, a new remote monitoring system, and new data generated from in-field experiments. The project will: 1) develop a new sensor calibration system and characterize signal artifacts that may influence detection accuracy; 2) develop new behavior detection algorithms using data captured in the lab; 3) conduct self-guided experiments in the field using the remote monitoring system proposed; and 4) refine recognition algorithms. Such sensitive measurements require ideal signal integrity, be sufficiently immune to signal artifacts, and tight electronics integration within wearable design constraints. This wearable system can profoundly impact the efficacy of habit reversal training during cognitive behavioral therapy, the leading method for reducing the negative effect of these behaviors.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.