# Remote monitoring using commercially available activity trackers and computer vision provides a holistic, low-cost assessment of Parkinson’s disease symptoms

> **NIH NIH K01** · UNIVERSITY OF IOWA · 2024 · $122,487

## Abstract

Although there has been considerable interest in using remote monitoring in diseases like Parkinson’s disease,
Alzheimer’s disease, and other Alzheimer’s disease-related dementias, there has been essentially no change
in clinical care. Yet, remote monitoring could radically reduce barriers to care, especially in rural areas – 80% of
rural areas medically underserved. The long-term goal is to use remote monitoring to improve the lives of
people with neurodegenerative causes of dementia. The overall objectives of this application are to identify the
value of wearable devices, automated fine-motor and speech assessments in detecting and measuring
cognitive and non-cognitive symptoms of Parkinson’s disease. The central hypothesis is that low-cost wearable
devices combined with computer vision and speech analysis can provide useful, holistic assessment of
Parkinson’s disease. The rationale for this project is that remote monitoring can increase the effectiveness of
expert care, alleviating barriers of access and distance in underserved, rural communities. The hypothesis will
be tested with two specific aims: 1) Identify the value of low-cost, holistic assessment for predicting Parkinson’s
disease diagnosis and cognitive impairment and 2) Identify the value of low-cost, holistic assessment for
predicting one-year cognitive, motor progression in Parkinson’s disease. In the first aim, people with possible
Parkinson’s disease will be provided an activity tracker and conduct home-based motor and speech
assessments with the goal of building a classifier to predict the ultimate diagnosis (Parkinson’s disease versus
not Parkinson’s disease) and cognitive status at baseline (normal cognitive, mild cognitive impairment,
dementia). The second aim will build a cohort of people recently diagnosed with Parkinson’s disease and
conduct a 4-week assessment using an activity tracking watch and home-based motor and speech
assessments. The objective will be to improve prediction of cognitive and motor symptoms at 1 year. The
proposed research is innovative because it focuses on using data collection using low-cost, commercially
available devices to construct a holistic measure of both the motor and cognitive manifestations of Parkinson’s
disease. The proposed research is significant because it is expected to provide a low-cost framework useful for
non-expert providers to screen for and evaluate Parkinson’s disease and to provide a more accurate prognosis
for people newly diagnosed. As a career development grant, this proposal is ideal: it builds on the applicant’s
past skills in health economics by adding knowledge of neuroscience, neurodegenerative diseases and
dementia, human subjects, and clinical research – all relatively novel areas for the applicant. The applicant will
accomplish these career development goals through both conducting the proposed research and didactic
instruction in clinical trials, neuroscience, and neuropathology. The applicant’s division and ins...

## Key facts

- **NIH application ID:** 10985288
- **Project number:** 1K01AG084844-01A1
- **Recipient organization:** UNIVERSITY OF IOWA
- **Principal Investigator:** Jacob Simmering
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $122,487
- **Award type:** 1
- **Project period:** 2024-08-09 → 2029-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10985288

## Citation

> US National Institutes of Health, RePORTER application 10985288, Remote monitoring using commercially available activity trackers and computer vision provides a holistic, low-cost assessment of Parkinson’s disease symptoms (1K01AG084844-01A1). Retrieved via AI Analytics 2026-06-12 from https://api.ai-analytics.org/grant/nih/10985288. Licensed CC0.

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