activity
20232026
most citedDifferential Private Federated Transfer Learning for Mental Health Monitoring in Everyday Settings: A Case Study on Stress Detection

6 citations · 13 across the 8 of their papers we have counts for

collaborators
Showing eess.SPShow all

5 papers · 1 filter

eess.SP2025

Multimodal Sleep Stage and Sleep Apnea Classification Using Vision Transformer: A Multitask Explainable Learning Approach

Kianoosh Kazemi, Iman Azimi, Michelle Khine +3

Sleep is an essential component of human physiology, contributing significantly to overall health and quality of life. Accurate sleep staging and disorder detection are crucial for…

eess.SP2024★ 5 cited

Loneliness Forecasting Using Multi-modal Wearable and Mobile Sensing in Everyday Settings

Zhongqi Yang, Iman Azimi, Salar Jafarlou +7

The adverse effects of loneliness on both physical and mental well-being are profound. Although previous research has utilized mobile sensing techniques to detect mental health iss…

eess.SP2024

ECG Unveiled: Analysis of Client Re-identification Risks in Real-World ECG Datasets

Ziyu Wang, Anil Kanduri, Seyed Amir Hossein Aqajari +5

While ECG data is crucial for diagnosing and monitoring heart conditions, it also contains unique biometric information that poses significant privacy risks. Existing ECG re-identi…

eess.SP2024

Robust CNN-based Respiration Rate Estimation for Smartwatch PPG and IMU

Kianoosh Kazemi, Iman Azimi, Pasi Liljeberg +1

Respiratory rate (RR) serves as an indicator of various medical conditions, such as cardiovascular diseases and sleep disorders. These RR estimation methods were mostly designed fo…

eess.SP2023★ 2 cited

Context-Aware Stress Monitoring using Wearable and Mobile Technologies in Everyday Settings

Seyed Amir Hossein Aqajari, Sina Labbaf, Phuc Hoang Tran +5

Daily monitoring of stress is a critical component of maintaining optimal physical and mental health. Physiological signals and contextual information have recently emerged as prom…