# Multi-objective Feature Selection in Remote Health Monitoring Applications

arXiv: https://arxiv.org/abs/2401.05538 · HTML: https://mlsanity.com/paper/2401.05538/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 34 references that are in the map.
- First posted on arXiv 10 Jan 2024.

## Builds on (most cited first, 5 of 5)

- [Face2PPG: An unsupervised pipeline for blood volume pulse extraction from faces](https://mlsanity.com/paper/2202.04101/) (2022)
- [Depression Recognition using Remote Photoplethysmography from Facial Videos](https://mlsanity.com/paper/2206.04399/) (2022)
- [Modeling the Trade-off of Privacy Preservation and Activity Recognition on Low-Resolution Images](https://mlsanity.com/paper/2303.10435/) (2023)
- [Privacy-Preserving Remote Heart Rate Estimation from Facial Videos](https://mlsanity.com/paper/2306.01141/) (2023)
- [Non-Contact Heart Rate Measurement from Deteriorated Videos](https://mlsanity.com/paper/2304.14789/) (2023)

## Abstract (arXiv)

Radio frequency (RF) signals have facilitated the development of non-contact human monitoring tasks, such as vital signs measurement, activity recognition, and user identification. In some specific scenarios, an RF signal analysis framework may prioritize the performance of one task over that of others. In response to this requirement, we employ a multi-objective optimization approach inspired by biological principles to select discriminative features that enhance the accuracy of breathing patterns recognition while simultaneously impeding the identification of individual users. This approach is validated using a novel vital signs dataset consisting of 50 subjects engaged in four distinct breathing patterns. Our findings indicate a remarkable result: a substantial divergence in accuracy between breathing recognition and user identification. As a complementary viewpoint, we present a contrariwise result to maximize user identification accuracy and minimize the system's capacity for breathing activity recognition.