Sensing, computing, and communications for energy harvesting IoTs: A survey

D Ma, G Lan, M Hassan, W Hu… - … Surveys & Tutorials, 2019 - ieeexplore.ieee.org
With the growing number of deployments of Internet of Things (IoT) infrastructure for a wide
variety of applications, the battery maintenance has become a major limitation for the …

Online fall detection using recurrent neural networks on smart wearable devices

M Musci, D De Martini, N Blago… - … on Emerging Topics …, 2020 - ieeexplore.ieee.org
Unintentional falls can cause severe injuries and even death, especially if no immediate
assistance is given. A fall detection system aims to detect a fall as soon as it occurs …

Embedded real-time fall detection with deep learning on wearable devices

E Torti, A Fontanella, M Musci, N Blago… - 2018 21st euromicro …, 2018 - ieeexplore.ieee.org
Unintentional falls are the leading cause of fatal injuries and nonfatal trauma among older
adults. An automated monitoring system that detects occurring falls and issues remote …

Home monitoring of motor fluctuations in Parkinson's disease patients

L Borzì, M Varrecchia, G Olmo, CA Artusi… - Journal of Reliable …, 2019 - Springer
In Parkinson's disease, motor fluctuations (worsening of tremor, bradykinesia, freezing of
gait, postural instability) affect up to 70% of patients within 9 years of l L-dopa therapy …

Embedding recurrent neural networks in wearable systems for real-time fall detection

E Torti, A Fontanella, M Musci, N Blago, D Pau… - Microprocessors and …, 2019 - Elsevier
Accidental falls are the preminent cause of fatal injuries and the most common cause of
nonfatal trauma-related hospital admissions among elderly adults. An automated monitoring …

Digital watermarking of ecg data for secure wireless commuication

S Kaur, R Singhal, O Farooq… - … conference on recent …, 2010 - ieeexplore.ieee.org
Use of wireless technology has made the bio-medical data vulnerable to attacks like
tampering, hacking etc. This paper proposes the use of digital watermarking to increase the …

Low-power HWAccelerator for AI edge-computing in human activity recognition systems

A De Vita, D Pau, C Parrella… - 2020 2nd IEEE …, 2020 - ieeexplore.ieee.org
In this paper, an energy efficient HW accelerator for AI edge-computing in Human Activity
Recognition is proposed. The system processes samples from a tri-axial accelerometer and …

Implementation of a binary neural network on a passive array of magnetic tunnel junctions

JM Goodwill, N Prasad, BD Hoskins, MW Daniels… - Physical Review …, 2022 - APS
The increasing scale of neural networks and their growing application space have produced
demand for more energy-and memory-efficient artificial-intelligence-specific hardware …

Experimental demonstration of a robust training method for strongly defective neuromorphic hardware

WA Borders, A Madhavan, MW Daniels… - arxiv preprint arxiv …, 2023 - arxiv.org
The increasing scale of neural networks needed to support more complex applications has
led to an increasing requirement for area-and energy-efficient hardware. One route to …

Deep recurrent neural networks for edge monitoring of personal risk and warning situations

E Torti, M Musci, F Guareschi, F Leporati… - Scientific …, 2019 - Wiley Online Library
Accidental falls are the main cause of fatal and nonfatal injuries, which typically lead to
hospital admissions among elderly people. A wearable system capable of detecting …