A 64-channel inductively-powered neural recording sensor array

This paper reports a 64-channel inductively powered neural recording sensor array. Neural signals are acquired, filtered, digitized and compressed in the channels. Additionally, each channel implements a local auto-calibration mechanism which configures the transfer characteristics of the recording site. The system has two operation modes; in one case the information captured by the channels is sent as uncompressed raw data; in the other, feature vectors extracted from the detected neural spikes are transmitted. Data streams coming from the channels are serialized by an embedded digital processor and transferred to the outside by means of the same inductive link used for powering the system. Simulation results show that the power consumption of the complete system is 377μW.Ministerio de Ciencia e Innovación TEC2009-0844

Phase Synchronization Operator for On-Chip Brain Functional Connectivity Computation

This paper presents an integer-based digital processor for the calculation of phase synchronization between two neural signals. It is based on the measurement of time periods between two consecutive minima. The simplicity of the approach allows for the use of elementary digital blocks, such as registers, counters, and adders. The processor, fabricated in a 0.18- μ m CMOS process, only occupies 0.05 mm 2 and consumes 15 nW from a 0.5 V supply voltage at a signal input rate of 1024 S/s. These low-area and low-power features make the proposed processor a valuable computing element in closed-loop neural prosthesis for the treatment of neural disorders, such as epilepsy, or for assessing the patterns of correlated activity in neural assemblies through the evaluation of functional connectivity maps.Ministerio de Economía y Competitividad TEC2016-80923-POffice of Naval Research (USA) N00014-19-1-215

A Wireless Neuroprosthesis for Patients with Drug-refractory Epilepsy:A Proof-of-Concept Study

Objective Acute or protracted cortical recording may be necessary for patients with drug-refractory epilepsy to identify the ictogenic regions before undergoing resection. Currently, these invasive recording techniques present certain limitations, one of which is the need for cables connecting the recording electrodes placed in the intracranial space with external devices displaying the recorded electrocorticographic signals. This equates to a direct connection between the sterile intracranial space with the non-sterile environment. Due to the increasing likelihood of infections with time, subdural grids are typically removed a few days after implantation, a limiting factor in localizing the epileptogenic zone if seizures are not frequent enough to be captured within this time-frame. Furthermore, patients are bound to stay in the hospital, connected by the wires to the recording device, thus increasing substantially the treatment costs. To address some of the current shortcomings of invasive monitoring, we developed a neuroprosthesis made of a subdural silicone grid connected to a wireless transmitter allowing prolonged electrocorticografic recording and direct cortical stimulation. This device consists of a silicone grid with 128-platinum/iridium contacts, connected to an implantable case providing wireless recording and stimulation. The case also houses a wirelessly rechargeable battery for chronic long-term implants. We report the results of the first human proof-of-concept trial for wireless transmission of electrocorticographic recordings using a device suited for long-term implantation in three patients with drug-refractory epilepsy. Methods Three patients with medically refractory epilepsy underwent the temporary intraoperative placement of the subdural grid connected to the wireless device for recording and transmission of electrocorticographic signals for a duration of five minutes before the conventional recording electrodes were placed or the ictal foci were resected. Results Wireless transmission of brain signals was successfully achieved. The wireless electrocorticographic signal was judged of excellent quality by a blinded neurophysiologist. Conclusions This preliminary experience reports the first successful placement of a wireless electrocorticographic recording device in humans. Long-term placement for prolonged wireless electrocorticographic recording in epilepsy patients will be the next step

Intra-Body Communications for Nervous System Applications: Current Technologies and Future Directions

The Internet of Medical Things (IoMT) paradigm will enable next generation healthcare by enhancing human abilities, supporting continuous body monitoring and restoring lost physiological functions due to serious impairments. This paper presents intra-body communication solutions that interconnect implantable devices for application to the nervous system, challenging the specific features of the complex intra-body scenario. The presented approaches include both speculative and implementative methods, ranging from neural signal transmission to testbeds, to be applied to specific neural diseases therapies. Also future directions in this research area are considered to overcome the existing technical challenges mainly associated with miniaturization, power supply, and multi-scale communications.Comment: https://www.sciencedirect.com/science/article/pii/S138912862300163

Recent Advances on Implantable Wireless Sensor Networks

Implantable electronic devices are undergoing a miniaturization age, becoming more efficient and yet more powerful as well. Biomedical sensors are used to monitor a multitude of physiological parameters, such as glucose levels, blood pressure and neural activity. A group of sensors working together in the human body is the main component of a body area network, which is a wireless sensor network applied to the human body. In this chapter, applications of wireless biomedical sensors are presented, along with state-of-the-art communication and powering mechanisms of these devices. Furthermore, recent integration methods that allow the sensors to become smaller and more suitable for implantation are summarized. For individual sensors to become a body area network (BAN), they must form a network and work together. Issues that must be addressed when developing these networks are detailed and, finally, mobility methods for implanted sensors are presented

Roadmap on semiconductor-cell biointerfaces.

This roadmap outlines the role semiconductor-based materials play in understanding the complex biophysical dynamics at multiple length scales, as well as the design and implementation of next-generation electronic, optoelectronic, and mechanical devices for biointerfaces. The roadmap emphasizes the advantages of semiconductor building blocks in interfacing, monitoring, and manipulating the activity of biological components, and discusses the possibility of using active semiconductor-cell interfaces for discovering new signaling processes in the biological world

Proposal of a health care network based on big data analytics for PDs

Health care networks for Parkinson's disease (PD) already exist and have been already proposed in the literature, but most of them are not able to analyse the vast volume of data generated from medical examinations and collected and organised in a pre-defined manner. In this work, the authors propose a novel health care network based on big data analytics for PD. The main goal of the proposed architecture is to support clinicians in the objective assessment of the typical PD motor issues and alterations. The proposed health care network has the ability to retrieve a vast volume of acquired heterogeneous data from a Data warehouse and train an ensemble SVM to classify and rate the motor severity of a PD patient. Once the network is trained, it will be able to analyse the data collected during motor examinations of a PD patient and generate a diagnostic report on the basis of the previously acquired knowledge. Such a diagnostic report represents a tool both to monitor the follow up of the disease for each patient and give robust advice about the severity of the disease to clinicians

Healthy aims: developing new medical implants and diagnostic equipment

Healthy Aims is a €23-million, four-year project, funded under the EU’s Information Society Technology Sixth Framework program to develop intelligent medical implants and diagnostic systems (www.healthyaims.org). The project has 25 partners from 10 countries, including commercial, clinical, and research groups. This consortium represents a combination of disciplines to design and fabricate new medical devices and components as well as to test them in laboratories and subsequent clinical trials. The project focuses on medical implants for nerve stimulation and diagnostic equipment based on straingauge technology