Back to search results

Remote Sensing for Alzheimer's Disease and Related Dementias (ADRD) Activities

This study is testing a "Remote Ambient Sensor System" to see if smart-home sensors can accurately identify daily activities in older adults with Alzheimer's Disease and Related Dementias (ADRD) or Mild Cognitive Impairment (MCI). These sensors, like motion and door contact sensors, are placed in your home and connected through a small computer and mobile hotspot. The goal is to use these sensors and artificial intelligence (AI) to help detect early symptoms and provide personalized support for people with ADRD. The study aims to enroll 16 participants aged 50 and older who have been diagnosed with MCI or mild dementia by a specialist. Success will be measured by how accurately the sensor system can classify daily activities within the first 1-4 weeks after you join. The current recruitment status is unclear.

Study design
This interventional study plans to enroll 16 participants. It is not specified if it is randomized or blinded.
What's involved
Not specified in the trial record.
Compensation
Not stated in the trial record.
Follow-up
The primary outcomes are measured within 1-4 weeks after enrollment.

AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.

NCT07120347

Remote Sensing for ADRD-Specific Activities Identification in Older Adults

Recruiting
NAAges 50+InterventionalSupportive care
University of Missouri-Columbia
~16 participants
Updated 2025-08-13 on ClinicalTrials.gov
What's tested:Remote Ambient Sensor System

At a glance

Recruiting sites
1 of 1 listed site is recruiting right now
RecruitingSuspended, closed, or not yet open
What they're measuring
Classification accuracy of ambient sensor-based daily activity models
Measured over Weeks 1-4 after enrollment
+2 more outcomes measured

Conditions

Alzheimer Disease and Related Dementias (ADRD)
Mild Cognitive Impairment (MCI)

Explore related trials

Alzheimer Disease and Related DementiasMild cognitive disorder

NCT07120347

Where you'd take part

This study runs at 1 site. They're the same protocol — you choose where, and that choice sets who your contact draft is addressed to.

  • University of Missouri

    Columbia, Missouristudy coordinator listed

    Recruiting

Sites open and close at different times, so the status above is per site — it can differ from the study's overall status.

Who to contact

Knoo Lee, PhD
[email protected]
5738840421
Email the study team

Opens a ready-to-send draft in your own email app — review before sending.

Want this trial checked against your situation?

Add a private profile and we'll compare every criterion below against your situation — and tell you which ones are met, uncertain, or excluding.

Check eligibility for this trial ~2 min · HIPAA-protected · delete anytime
Eligibility criteria

Inclusion

Community-dwelling, English-speaking adults aged ≥ 50 years
Clinical diagnosis of mild cognitive impairment or mild dementia (ADRD)
Diagnosis established by a neuropsychologist, neurologist, or geriatrician within the University of Missouri Healthcare System
Diagnosis confirmed using the latest consensus criteria and verified through record review
No restriction on the etiology of the cognitive disorder (e.g., Alzheimer's disease, vascular dementia, mixed dementia)

Exclusion

Clinical Dementia Rating (CDR) global score \> 1 (moderate or severe dementia)
Cognitive or functional impairments that would preclude meaningful participation in daily activities

What this trial measures

  • Classification accuracy of ambient sensor-based daily activity modelsWeeks 1-4 after enrollment

    Percent of daily activity labels correctly predicted by SVM, XGBoost, LSTM and Transformer models, trained and tested on ambient motion and environmental sensor data collected during weeks 1-4 from participants with and without early-stage ADRD.

  • F1 score of ambient sensor-based daily activity modelsWeeks 1-4 after enrollment

    Harmonic mean of precision and recall for SVM, XGBoost, LSTM and Transformer models, evaluated on held-out portions of the week 1-4 ambient sensor data.

  • Area under the ROC curve of ambient sensor-based daily activity modelsWeeks 1-4 after enrollment

    AUC of ROC curves for SVM, XGBoost, LSTM and Transformer models distinguishing among daily activity classes, based on training and testing using weeks 1-4 ambient sensor readings.