Syed Yaseen Shah

TL;DR: Continuous monitoring ADLs and classification freezing of gait episodes using Wi-Fi and radar imaging to exploit the multi-resolution scalograms generated by channel state information (CSI) imprint and micro-Doppler signatures produced by reflected radar signal.

TL;DR: Radar images to detect large scale body movements is looked at and results showed how Principal Component Analysis was most beneficial when the training data was expanded by augmentation of the available data.

TL;DR: In this paper , the authors discuss the current literature on invasive/contact and non-invasive/non-contact technologies (including Wi-Fi, radar, and software-defined radio) that have been effectively used to detect, diagnose, and monitor human activities and COVID-19 related symptoms, such as irregular respiration.

TL;DR: A novel, non-wearable, device-free, privacy-preserving Wi-Fi imaging-based occupancy detection system for future smart buildings and a novel encryption algorithm using Chirikov and Intertwining map-based is proposed to encrypt the scalogram images.

TL;DR: A system that can effectively detect fall/collapse and classify other discrete daily living activities such as sitting, standing, walking, drinking, and bending is developed using a publicly accessible dataset.