Application of artificial intelligence in wearable devices: Opportunities and challenges
D Nahavandi, R Alizadehsani, A Khosravi… - Computer Methods and …, 2022 - Elsevier
Background and objectives: Wearable technologies have added completely new and fast
emerging tools to the popular field of personal gadgets. Aside from being fashionable and …
emerging tools to the popular field of personal gadgets. Aside from being fashionable and …
Recent advancements in emerging technologies for healthcare management systems: a survey
In recent times, the growth of the Internet of Things (IoT), artificial intelligence (AI), and
Blockchain technologies have quickly gained pace as a new study niche in numerous …
Blockchain technologies have quickly gained pace as a new study niche in numerous …
Real-time ultra-low power ECG anomaly detection using an event-driven neuromorphic processor
Accurate detection of pathological conditions in human subjects can be achieved through off-
line analysis of recorded biological signals such as electrocardiograms (ECGs). However …
line analysis of recorded biological signals such as electrocardiograms (ECGs). However …
ECG classification algorithm based on STDP and R-STDP neural networks for real-time monitoring on ultra low-power personal wearable devices
A Amirshahi, M Hashemi - IEEE transactions on biomedical …, 2019 - ieeexplore.ieee.org
This paper presents a novel ECG classification algorithm for inclusion as part of real-time
cardiac monitoring systems in ultra low-power wearable devices. The proposed solution is …
cardiac monitoring systems in ultra low-power wearable devices. The proposed solution is …
Mapping spiking neural networks to neuromorphic hardware
Neuromorphic hardware implements biological neurons and synapses to execute a spiking
neural network (SNN)-based machine learning. We present SpiNeMap, a design …
neural network (SNN)-based machine learning. We present SpiNeMap, a design …
A recipe for creating ideal hybrid memristive-CMOS neuromorphic processing systems
E Chicca, G Indiveri - Applied Physics Letters, 2020 - pubs.aip.org
The development of memristive device technologies has reached a level of maturity to
enable the design and fabrication of complex and large-scale hybrid memristive …
enable the design and fabrication of complex and large-scale hybrid memristive …
Implementing spiking neural networks on neuromorphic architectures: A review
Recently, both industry and academia have proposed several different neuromorphic
systems to execute machine learning applications that are designed using Spiking Neural …
systems to execute machine learning applications that are designed using Spiking Neural …
Futuristic biosensors for cardiac health care: an artificial intelligence approach
Biosensor-based devices are pioneering in the modern biomedical applications and will be
the future of cardiac health care. The coupling of artificial intelligence (AI) for cardiac …
the future of cardiac health care. The coupling of artificial intelligence (AI) for cardiac …
Endurance-aware mapping of spiking neural networks to neuromorphic hardware
Neuromorphic computing systems are embracing memristors to implement high density and
low power synaptic storage as crossbar arrays in hardware. These systems are energy …
low power synaptic storage as crossbar arrays in hardware. These systems are energy …
PyCARL: A PyNN interface for hardware-software co-simulation of spiking neural network
We present PyCARL, a PyNN-based common Python programming interface for hardware-
software co-simulation of spiking neural network (SNN). Through PyCARL, we make the …
software co-simulation of spiking neural network (SNN). Through PyCARL, we make the …