Wednesday, December 31, 2025 12/31/2025

SCH: Personalized Depression Treatment Support by Mobile Sensor Analytics

Award Number: R01MH119678
ORGANIZATION: NATIONAL INSTITUTE OF MENTAL HEALTH
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 07/18/2019
PERIOD OF PERFORMANCE END DATE: 06/30/2025

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SCH: Personalized Depression Treatment Support by Mobile Sensor Analytics - The current best practice guidelines for treating depression call for close monitoring of patients, and periodically adjusting treatment as needed. This project will advance personalized depression treatment by developing an innovative system, DepWatch, that leverages mobile health technologies and machine learning tools to provide clinicians objective, accurate, and timely assessment of depression symptoms to assist with their clinical decision making process. Specifically, DepWatch collects sensory data passively from smartphones and wristbands, without any user interaction, and uses simple user-friendly interfaces to collect ecological momentary assessments (EMA), medication adherence and safety related data from patients. The collected data will be fed to machine learning models to be developed in the project to provide weekly assessment of patient symptom levels and predict the trajectory of treatment response over time. The assessment and prediction results are then presented using a graphic interface to clinicians to help them make critical treatment decisions. Our project comprises two studies. Phase I collects sensory data and other data (e.g., clinical data, EMA, tolerability and safety data) from 250 adult participants with unstable depression symptomatology. The data thus collected will be used to develop and validate assessment and prediction models, which will be incorporated into DepWatch system. In Phase II, three clinicians will use DepWatch to support their clinical decision making process; a total of 50 participants under treatment by the three participating clinicians will be recruited for the study. A number of innovative machine learning techniques will be developed. These include a set of new learning formulations to construct matrix-based longitudinal predictive models, and determine the temporal contingency and the most influential features, and deep learning based data imputation methods that can handle both problems of sporadic missing data as well as missing data in an entire view. In addition, multi-task feature learning models and feature selection techniques will be expanded and refined for this challenging setting of large-scale heterogeneous data.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = -$156 )
2026	2023	UNIVERSITY OF CONNECTICUT	438 WHITNEY RD EXTENSION UNIT 1133	STORRS	CT	06269	CAPITOL	USA	Mental Health Research Grants	000	4	11/28/2025	NON-COMPETING CONTINUATION	-$156
														Subtotal = -$156

Issue Date FY: 2024 ( Subtotal = $0 )
2024	2023	UNIVERSITY OF CONNECTICUT	438 WHITNEY RD EXTENSION UNIT 1133	STORRS	CT	06269	CAPITOL	USA	Mental Health Research Grants	000	4	7/19/2024	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2023 ( Subtotal = $233,742 )
2023	2023	UNIVERSITY OF CONNECTICUT	438 WHITNEY RD EXTENSION UNIT 1133	STORRS	CT	06269	CAPITOL	USA	Mental Health Research Grants	000	4	6/29/2023	NON-COMPETING CONTINUATION	$233,742
														Subtotal = $233,742

Issue Date FY: 2022 ( Subtotal = $0 )
2022	2021	UNIVERSITY OF CONNECTICUT	438 WHITNEY RD EXTENSION UNIT 1133	STORRS	CT	06269	CAPITOL	USA	Mental Health Research Grants	000	3	7/11/2022	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2021 ( Subtotal = $245,551 )
2021	2021	UNIVERSITY OF CONNECTICUT	438 WHITNEY RD EXTENSION UNIT 1133	STORRS	CT	06269	CAPITOL	USA	Mental Health Research Grants	000	3	6/4/2021	NON-COMPETING CONTINUATION	$245,551
														Subtotal = $245,551

Issue Date FY: 2020 ( Subtotal = $270,271 )
2020	2020	UNIVERSITY OF CONNECTICUT	438 WHITNEY RD EXTENSION UNIT 1133	STORRS	CT	06269	CAPITOL	USA	Mental Health Research Grants	000	2	6/17/2020	NON-COMPETING CONTINUATION	$270,271
														Subtotal = $270,271

Issue Date FY: 2019 ( Subtotal = $292,411 )
2019	2019	UNIVERSITY OF CONNECTICUT	438 WHITNEY RD EXTENSION UNIT 1133	STORRS	CT	06269	CAPITOL	USA	Mental Health Research Grants	001	1	7/29/2019	NEW	$0
2019	2019	UNIVERSITY OF CONNECTICUT	438 WHITNEY RD EXTENSION UNIT 1133	STORRS	CT	06269	CAPITOL	USA	Mental Health Research Grants	000	1	7/18/2019	NEW	$292,411
2019	2019	UNIVERSITY OF CONNECTICUT	438 WHITNEY RD EXTENSION UNIT 1133	STORRS	CT	06269	CAPITOL	USA	Mental Health Research Grants	002	1	9/25/2019	NEW	$0
														Subtotal = $292,411

Grand Total All Awards = $1,041,820

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SCH: Personalized Depression Treatment Support by Mobile Sensor Analytics

Award Number: R01MH119678

ORGANIZATION: NATIONAL INSTITUTE OF MENTAL HEALTH

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 07/18/2019

PERIOD OF PERFORMANCE END DATE: 06/30/2025

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