BIOWISH: Biometric Recognition using Wearable Inertial Sensors detecting Heart Activity
Emanuele Maiorana, Chiara Romano, Emiliano Schena, and Carlo Massaroni

TL;DR
This paper introduces BIOWISH, a biometric recognition method using wearable inertial sensors detecting heart activity through mechanical signals, demonstrating high accuracy with short recordings across multiple activities.
Contribution
The study pioneers the use of inertial sensors for biometric recognition based on mechanical heart signals, expanding beyond electrical and optical methods.
Findings
High recognition accuracy achieved with short-time chest vibration recordings.
Effective differentiation between legitimate and impostor subjects using deep learning.
Robust performance across different activities and sessions.
Abstract
Wearable devices are increasingly used, thanks to the wide set of applications that can be deployed exploiting their ability to monitor physical activity and health-related parameters. Their usage has been recently proposed to perform biometric recognition, leveraging on the uniqueness of the recorded traits to generate discriminative identifiers. Most of the studies conducted on this topic have considered signals derived from cardiac activity, detecting it mainly using electrical measurements thorugh electrocardiography, or optical recordings employing photoplethysmography. In this paper we instead propose a BIOmetric recognition approach using Wearable Inertial Sensors detecting Heart activity (BIOWISH). In more detail, we investigate the feasibility of exploiting mechanical measurements obtained through seismocardiography and gyrocardiography to recognize a person. Several feature…
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Taxonomy
TopicsNon-Invasive Vital Sign Monitoring · Healthcare Technology and Patient Monitoring · Context-Aware Activity Recognition Systems
