Radar signal processing for sensing in assisted living: the challenges associated with real-time implementation of emerging algorithms

This article covers radar signal processing for sensing in the context of assisted living (AL). This is presented through three example applications: human activity recognition (HAR) for activities of daily living (ADL), respiratory disorders, and sleep stages (SSs) classification. The common challenge of classification is discussed within a framework of measurements/preprocessing, feature extraction, and classification algorithms for supervised learning. Then, the specific challenges of the three applications from a signal processing standpoint are detailed in their specific data processing and ad hoc classification strategies. Here, the focus is on recent trends in the field of activity recognition (multidomain, multimodal, and fusion), health-care applications based on vital signs (superresolution techniques), and comments related to outstanding challenges. Finally, this article explores challenges associated with the real-time implementation of signal processing/classification algorithms

A Neuromorphic Prosthesis to Restore Communication in Neuronal Networks

Recent advances in bioelectronics and neural engineering allowed the development of brain machine interfaces and neuroprostheses, capable of facilitating or recovering functionality in people with neurological disability. To realize energy-efficient and real-time capable devices, neuromorphic computing systems are envisaged as the core of next-generation systems for brain repair. We demonstrate here a real-time hardware neuromorphic prosthesis to restore bidirectional interactions between two neuronal populations, even when one is damaged or missing. We used in vitro modular cell cultures to mimic the mutual interaction between neuronal assemblies and created a focal lesion to functionally disconnect the two populations. Then, we employed our neuromorphic prosthesis for bidirectional bridging to artificially reconnect two disconnected neuronal modules and for hybrid bidirectional bridging to replace the activity of one module with a real-time hardware neuromorphic Spiking Neural Network. Our neuroprosthetic system opens avenues for the exploitation of neuromorphic-based devices in bioelectrical therapeutics for health care