Miniaturised Wireless Power Transfer Systems for Neurostimulation: A Review

In neurostimulation, wireless power transfer is an efficient technology to overcome several limitations affecting medical devices currently used in clinical practice. Several methods were developed over the years for wireless power transfer. In this review article, we report and discuss the three most relevant methodologies for extremely miniaturised implantable neurostimulator: ultrasound coupling, inductive coupling and capacitive coupling. For each powering method, the discussion starts describing the physical working principle. In particular, we focus on the challenges given by the miniaturisation of the implanted integrated circuits and the related ad-hoc solutions for wireless power transfer. Then, we present recent developments and progresses in wireless power transfer for biomedical applications. Last, we compare each technique based on key performance indicators to highlight the most relevant and innovative solutions suitable for neurostimulation, with the gaze turned towards miniaturisation

In-vivo monitoring for electrical expression of plant living parameters by an impedance lab system

We present a complete in-lab system to monitor the plant and its surrounding environment. The plant impedance is directly measured in a continuous manner, while, simultaneously surrounding environment parameters known to affect plant status, are monitored. This is done combining a new in-vivo direct measurement of the plant together with an embedded system using available sensor technology and a designated interface for continuous data acquisition. Furthermore, the next versions this system can be deployed as a field monitoring device, with simple adaptations

Assessing the feasibility of augmenting fall detection systems by relying on UWB-based position tracking and a home robot

Falls in the home environment are a primary cause of injury in older adults. According to the U.S. Centers for Disease Control and Prevention, every year, one in four adults 65 years of age and older reports experiencing a fall. A variety of different technologies have been proposed to detect fall events. However, the need to detect all fall instances (i.e., to avoid false negatives) has led to the development of systems marked by high sensitivity and hence a significant number of false alarms. The occurrence of false alarms causes frequent and unnecessary calls to emergency response centers, which are critical resources that should be utilized only when necessary. Besides, false alarms decrease the level of confidence of end-users in the fall detection system with a negative impact on their compliance with using the system (e.g., wearing the sensor enabling the detection of fall events). Herein, we present a novel approach aimed to augment traditional fall detection systems that rely on wearable sensors and fall detection algorithms. The proposed approach utilizes a UWB-based tracking system and a home robot. When the fall detection system generates an alarm, the alarm is relayed to a base station that utilizes a UWB-based tracking system to identify where the older adult and the robot are so as to enable navigating the environment using the robot and reaching the older adult to check if he/she experienced a fall. This approach prevents unnecessary calls to emergency response centers while enabling a tele-presence using the robot when appropriate. In this paper, we report the results of a novel fall detection algorithm, the characteristics of the alarm notification system, and the accuracy of the UWB-based tracking system that we implemented. The fall detection algorithm displayed a sensitivity of 99.0% and a specificity of 97.8%. The alarm notification system relayed all simulated alarm notification instances with a maximum delay of 106 ms. The UWB-based tracking system was found to be suitable to locate radio tags both in line-of-sight and in no-line-of-sight conditions. This result was obtained by using a machine learning-based algorithm that we developed to detect and compensate for the multipath effect in no-line-of-sight conditions. When using this algorithm, the error affecting the estimated position of the radio tags was smaller than 0.2 m, which is satisfactory for the application at hand

Live Wire - A Low-Complexity Body Channel Communication System for Landmark Identification

This paper presents a robust simplex Body Channel Communication (BCC) system aimed at providing an interactive infrastructure solution for visually impaired people. Compared to existing BCC solutions, it provides high versatility, weara- bility and installability in an environment in a low complexity hardware-software solution. It operates with a ground referred transmitter (TX) and it is based on an asynchronous thresh- old receiver (RX) architecture. Synchronization, demodulation and packetizing and threshold control are completely software defined and implemented using MicroPython. The RX includes Bluetooth® (BT) radio connectivity and a cell-phone application provides push text-to-speech notifications to a smartphone. The hardware achieves a Packet Error Rate (PER) of ∼0.1 at 550 kHz pulse center frequency, Synchronized-On Off Keying (S- OOK) modulation and 1 kbps data rate, for an average current consumption of 44mA

Impulse-based asynchronous serial communication protocol on optical fiber link for AER systems

We developed an Impulse-Based Asynchronous Serial Address-Event Representation (IB-AS-AER) protocol. It allows for full-duplex communication and explicit flow control, does not require any clock data recovery or accurate clock relationship between the transmitter and receiver. Moreover, the optical fiber communication link, that galvanically isolates the communicating devices, highly improves the robustness to electromagnetic disturbances, reduces the power consumption and allows for high data rate transmissions. In addition, the proposed implementation does not require any specific hardware and can be developed on low-cost FPGAs as well as on full-custom ASICs. Preliminary tests performed at 100 Mbps raw bit transfer rate confirm a 32 bit maximum event rate of 2.9 Meps

EO-ALERT: A Novel Architecture for the Next Generation of Earth Observation Satellites Supporting Rapid Civil Alerts

The EO-ALERT project proposes the definition and development of the next-generation Earth Observation (EO) data processing chain, based on a novel flight segment architecture that moves opti-mised key EO data processing elements from the ground segment to on-board the satellite, with the aim of delivering EO products to the end user with very low latency. EO-ALERT achieves, globally, latencies below five minutes for EO products delivery, and below 1 minute in some scenarios. The proposed archi-tecture combines innovations in the on-board elements of the data chain and the communications, namely: on-board reconfigurable data handling, on-board image generation and processing for the generation of alerts (EO products) using Artificial Intelligence (AI), on-board AI-based data compression and encryption, high-speed on-board avionics, and reconfigurable high data rate communication links to ground, including a separate chain for alerts with minimum latency and global coverage. This paper pre-sents the proposed architecture, its performance and hardware, considering two different user scenarios: ship detection and extreme weather nowcasting. The results show that, when implemented using COTS components and available communication links, the proposed architecture can deliver alerts to ground with latency below five minutes, for both SAR and Optical missions, demonstrating the viability of the EO-ALERT concept

A Novel Satellite Architecture for the Next Generation of Earth Observation Satellites Supporting Rapid Alerts

The EO-ALERT European Commission H2020 project proposes the definition, development, and verification and validation through ground hardware testing, of a next-generation Earth Observation (EO) data processing chain. The proposed data processing chain is based on a novel flight segment architecture that moves EO data processing elements traditionally executed in the ground segment to on-board the satellite, with the aim of delivering EO products to the end user with very low latency. EO-ALERT achieves, globally, latencies below five minutes for EO products delivery, and below one minute in realistic scenarios. The proposed EO-ALERT architecture is enabled by on-board processing, recent improvements in processing hardware using Commercial Off-The-Shelf (COTS) components, and persistent space-to-ground communications links. EO-ALERT combines innovations in the on-board elements of the data chain and the communications, namely: on-board reconfigurable data handling, on-board image generation and processing for the generation of alerts (EO products) using Machine Learning (ML) and Artificial Intelligence (AI), on-board AI-based data compression and encryption, high-speed on-board avionics, and reconfigurable high data rate communication links to ground, including a separate chain for alerts with minimum latency and global coverage. This paper presents the proposed architecture, its hardware realization for the ground testing in a representative environment and its performance. The architecture’s performance is evaluated considering two different user scenarios where very low latency (almost-real-time) EO product delivery is required: ship detection and extreme weather monitoring/nowcasting. The hardware testing results show that, when implemented using COTS components and available communication links, the proposed architecture can deliver alerts to the end user with a latency below five minutes, for both SAR and Optical missions, demonstrating the viability of the EO-ALERT architecture. In particular, in several test scenarios, for both the TerraSAR-X SAR and DEIMOS-2 Optical Very High Resolution (VHR) missions, hardware testing of the proposed architecture has shown it can deliver EO products and alerts to the end user globally, with latency lower than one-point-five minutes