UMN Office of Technology Commercialization

Research Progress Report · Ambient Intelligence Fall Detection System

Last updatedQ2 2025
EVT-0.1
Hardware revision
57
BOM components
Class B
IEC 62304 SW class
Class II
FDA device class
15
21 CFR 820 subparts
Q3 2025
Target IRB submission

Project Summary

Ambient Intelligence is developing a passive fall-detection and resident monitoring system for skilled nursing facilities (SNFs) using 60 GHz FMCW radar sensors (TI IWR6843AOP). The system captures radar point-cloud data, classifies activity and fall events using a custom machine learning algorithm, and surfaces real-time alerts and AI-generated narrative summaries to nursing staff via a web dashboard.

The fall-detection algorithm is classified as Software as a Medical Device (SaMD) under FDA guidance, targeting 510(k) clearance under 21 CFR 882. The development process follows IEC 62304 software lifecycle requirements and ISO 14971 risk management, with quality system documentation structured against 21 CFR Part 820.

The current phase focuses on bench validation of the detection algorithm, IRB protocol preparation for an observational pilot study at a partner SNF, and pre-submission engagement with FDA. Technology commercialization strategy is being developed in parallel with UMN OTC.

System Engineering

10 complete2 in progress3 planned67% done

Hardware EVT-0.1 assembled. Algorithm v0.1 trained. Cloud pipeline operational. Bench validation in progress.

IRB Approval Process

3 complete1 in progress5 planned33% done

Protocol and privacy analysis complete. Application preparation in progress. IRB submission targeted Q3 2025.