MoSHI-Led Projects


Remote Oncology Symptom Assessment (ROSA) 
PI: Carissa Low
Funding: NCI R37CA242545
Objective: (1) To develop a system to use mobile sensing to passively monitor patient-reported symptom burden during chemotherapy and (2) to evaluate the feasibility of using this system to generate automated clinical alerts. 

Sensing Activity and Gait in Elderly Survivors (SAGES) 
PIs: Carissa Low & Grace Campbell 
FundingPitt Pepper Center Pilot & Duquesne Faculty Development Award
Objective: To examine the association between continuous mobile sensor data features and commonly used measures of physical function in cancer survivors aged 65 and older. 

Musculoskeletal Oncology Virtual Evaluation Study (MOVES)
PIsKurt Weiss & Carissa Low 
FundingShadyside Hospital Foundation 
Objective: (1) To use mobile technology to assess pain, physical functioning, sleep, and depression as well as objective physical mobility patterns before and after intramedullary nailing procedures for metastatic bone disease and (2) to evaluate the potential clinical benefits of giving orthopedic oncology providers access to an online dashboard visualizing sensor and patient-reported data. 


Detecting Activity to Support Healing (DASH) 
PI: Carissa Low 
Funding: NCI K07CA204380 
Objective: To refine and test a novel technology-supported intervention to reduce sedentary behavior before and after abdominal cancer surgery. 

Computational Modeling of Behavioral Rhythms to Predict Readmissions 
PIsAnind Dey & Carissa Low 
FundingPittsburgh Health Data Alliance 
Objective: To develop computational models using passively-sensed behavioral data collected before and after pancreatic cancer surgery to predict real-time readmission risk. 

Collaborative Projects:

Capturing Habits and Everyday Experiences with Alcohol in Real-time Study (CHEEARS) 
PIAidan Wright 
Funding: NIAAA R01AA026879 
Objective: To apply machine learning to data collected from daily surveys and passive smartphone sensors in young adult risky drinkers to develop personalized models of problematic alcohol use.   

Predicting recurrences in bipolar illness (PROMPT-BD) 
PIBoris Birmaher 
Funding: NIMH R01MH126991 
Objective: To use passive sensing of sleep, activity, and sociability to improve prediction of mood recurrences in youth with bipolar illness. 

Connectomic Phenotyping of the Mood Switch in Bipolar Disorder (BDLONG) 
PIDanella Hafeman 
Objective: To use passive smartphone sensing to predict changes between euthymia, mania, and depression in teenagers and young adults with rapid cycling bipolar disorder. 

Targeting Stress Study (TSS) 
PI: Emily Lindsay 
Funding: NCCIH K01AT011232 
Objective: To refine a smartphone-based mindfulness intervention for adults with a history of early life adversity.   

Predicting alcohol use events in people with AUD using mobile sensors:  Towards automated telehealth treatment 
PIWalter Roberts, Yale University 
FundingAlkermes Pathways Research Award 
Objective:To develop predictive models of alcohol use events in adults with severe alcohol use disorder using physiological, behavioral, and environmental sensing. 

Mobile technology to track activity during vestibular rehabilitation 
PIBrooke Klatt 
FundingSHRS Dean’s Research and Development Award 
Objective: To characterize associations between activity and impairments before and after vestibular rehabilitation. 

The Impact of Social Media Use on Precursors of Adolescent Suicide Risk:  A Prospective Study 
PIJessica Hamilton, Rutgers University 
FundingNIMH K01MH121584 
Objective: To harness smartphone technology to examine whether social media use patterns predict sleep disruption, depressive symptoms, and suicidal ideation in adolescents.