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Portable and implantable electronics are becoming increasingly important in the healthcare sector. One of the challenges is to guarantee stable systems for longer periods of time. If we consider applications such as electrical nerve stimulation or implanted ion pumps, the requirements for, e.g., levels, duration, etc., vary over time, and there may be a need to be able to remotely reconfigure devices, which in turn extends the life of the implant. This dissertation studies the efficient healthcare wireless network, wireless power supply, and its use in implantable biomedical systems. The body-area network (BAN) and near-field communication (NFC) are studied. Several Application Specific Integrated Circuits (ASICs) solutions are implemented, manufactured, and characterized. ASICs for portable and implantable sensors and actuators still have high research value. In addition, advances in flexible, implantable inductive coils, along with near-field energy harvesting technology, have driven the development of wireless, implantable devices. The ASICs are used to initiate and generate controlled signals that govern actuators in multiple locations in the body. Electronics specifications may include operations related to tissue-specific absorption rate, stimulation duration or levels to avoid tissue temperature rise, power transmission distance, and controlled current or voltage drivers. In this work, the feasibility of BAN as a healthcare network has been investigated. The functionality of an existing BodyCom communication system was expanded, sensors and actuators are added. The system enables data transfer between several sensor nodes placed on a human body. In BAN, the information is propagated along the skin in a capacitive, electric field. The network was demonstrated with a sensor node (stretchable glove) and implantable ion pump (actuator) for drug delivery. With the stretchable glove, movement patterns could be captured, and ions were delivered from a reservoir i

This paper presents a nerve stimulation system implementation that contains full-wave rectifier-based energy harvester switching at 13.56MHz to generate stimulation current for accelerating the regeneration time of recovering damaged nerve. Reconfigurable eight-bit driver cells provide the selective option of controlling the stimulation current from as low as 4 mu A up to 0.92mA. The design is implemented in a standard 180nm CMOS process with a core area of 0.22mm(2) excluding a 3.6nF on-chip integrated capacitor which occupies 0.34mm(2) of the chip area. The fabricated chip is measured and characterized with coupled AC input amplitude of 2.2V and a driver load of 1k Omega. Furthermore, the measurement results verify the rectified DC output of 2V which implies a conversion ratio of 0.91.

Body area networks (BANs), cloud computing, and machine learning are platforms that can potentially enable advanced healthcare outside the hospital. By applying distributed sensors and drug delivery devices on/in our body and connecting to such communication and decision-making technology, a system for remote diagnostics and therapy is achieved with additional autoregulation capabilities. Challenges with such autarchic on-body healthcare schemes relate to integrity and safety, and interfacing and transduction of electronic signals into biochemical signals, and vice versa. Here, we report a BAN, comprising flexible on-body organic bioelectronic sensors and actuators utilizing two parallel pathways for communication and decision-making. Data, recorded from strain sensors detecting body motion, are both securely transferred to the cloud for machine learning and improved decision-making, and sent through the body using a secure body-coupled communication protocol to auto-actuate delivery of neurotransmitters, all within seconds. We conclude that both highly stable and accurate sensing-from multiple sensors-are needed to enable robust decision making and limit the frequency of retraining. The holistic platform resembles the self-regulatory properties of the nervous system, i.e., the ability to sense, communicate, decide, and react accordingly, thus operating as a digital nervous system., Funding Agencies|Linkoping University

Inductively powered 99% accurate implantable temperature sensor is designed, characterized and the findings are presented in this paper. The implantable sensors deliver a continuous temperature reading to external storage or readout devices via Near Field Communication interface. A 2.76 mu H rectangular inductive coil printed on a thin biocompatible plastic substrate is designed to establish the coupling link through NFC interface with external readout devices. A commercially available wide range temperature sensor chip is mounted along with the developed inductive coil on the same plastic substrate. For 50 samples, the received signal strength indicator, temperature accuracy and statistical distribution of measurement levels is investigated. Comparison of predetermined temperature in a controlled temperature and humidity chamber versus the temperature reading from the developed sensors proves a 99% accuracy., Funding Agencies|Swedish Foundation for Strategic Research (SSF)Swedish Foundation for Strategic Research

In this paper, a built-in-self-calibration RF amplitude detector circuit in 65 nm CMOS is presented. The proposed architecture makes use of two detector replicas with a feedback control system to perform the self-calibration. The system is capable of detecting RF peak amplitudes range of 0-0.6 V-p with a conversion gain of - 3 V/V. The proposed system has a wide dynamic range that can auto-corrects the RF detector to less than 10% across process and temperature variations. This architecture is implemented in standard 65 nm 1P7 M CMOS process. Comprehensive silicon measurement results show that the self-calibration structure improves the detection error of the non-calibrated RF amplitude detector by a maximum of 71% at only 230 mu W overall power consumption. The proposed system can be used to calibrate the variations in circuits within an RF transceiver such as LNA, Mixers, oscillators etc.