An integrated CMOS ultrawideband wireless telemetry transceiver for wearable and implantable medical sensor applications is reported in this letter. This high duty cycled, noncoherent transceiver supports scalable data rate up to 10 Mb/s with energy efficiency of 0.35 nJ/bit and 6.2 nJ/bit for transmitter and receiver, respectively. A prototype wireless capsule endoscopy using the proposed transceiver demonstrated in vivo image transmission of 640 × 480 resolution at a frame rate of 2.5 frames/s with 10 Mb/s data rate.

This paper presents a rectifier-less AC-DC energy harvesting circuit capable of harvesting energy from multiple low-voltage Piezoelectric Transducers (PETs). Synchronous electric charge extraction (SECE) technique, with bi-directional switches is adopted to achieve rectifier-less AC/DC direct conversion. The inductor is engaged only during the voltage peak of the PET output for a short period of time and therefore, a single inductor can be shared by multiple transducers. A split-capacitor charging topology is employed to harvest both positive and negative half-cycle energies, without the use of an input rectifier. In addition, a self-startup function is incorporated to kick-start the system from low input voltages. A prototype has been implemented with off-the-shelf components. Energy harvesting from three PET energy sources with different resonance frequencies is demonstrated. A peak overall power conversion efficiency of 79% is achieved with a system self-startup voltage of 650 mV.

Individuals with tetraplegia lack independent mobility, making them highly dependent on others to move from one place to another. Here, we describe how two macaques were able to use a wireless integrated system to control a robotic platform, over which they were sitting, to achieve independent mobility using the neuronal activity in their motor cortices. The activity of populations of single neurons was recorded using multiple electrode arrays implanted in the arm region of primary motor cortex, and decoded to achieve brain control of the platform. We found that free-running brain control of the platform (which was not equipped with any machine intelligence) was fast and accurate, resembling the performance achieved using joystick control. The decoding algorithms can be trained in the absence of joystick movements, as would be required for use by tetraplegic individuals, demonstrating that the non-human primate model is a good pre-clinical model for developing such a cortically-controlled movement prosthetic. Interestingly, we found that the response properties of some neurons differed greatly depending on the mode of control (joystick or brain control), suggesting different roles for these neurons in encoding movement intention and movement execution. These results demonstrate that independent mobility can be achieved without first training on prescribed motor movements, opening the door for the implementation of this technology in persons with tetraplegia.

A novel wideband hybrid dielectric resonator antenna structure comprises a rectangular dielectric resonator (DR) and a coplanar waveguide (CPW) inductive slot is proposed. In this configuration, the CPW inductive slot simultaneously acts as an effective radiator and the feeding structure of the DR. Dual resonances of the two radiators are merged to extend the antenna's bandwidth. A parametric study is performed to optimize the antenna performance and a prototype for 5-GHz WLAN application has been built and tested.

We present a fully implantable neural recording IC with a spike-driven data compression scheme to improve the power efficiency and preserve crucial data for monitoring brain activities. A difference between two consecutive neural signals, Δ-neural signal, is sampled in each channel to reduce the full dynamic range and the required resolution of an analog-to-digital converter (ADC), enabling the whole analog chain to be operated at a 0.5-V supply. A set of multiple Δ-signals are stored in analog memory to extract the magnitude and frequency features of the incoming neural signals, which are utilized to discriminate spikes in these signals instantaneously after the acquisition in the analog domain. The energy- and area-efficient successive approximation ADC is implemented and only converts detected spikes, decreasing the power dissipation and the amount of neural data. A prototype 16-channel neural interface IC was fabricated using a 0.18-μm CMOS process, and each component in the analog front-end was fully characterized. We successfully demonstrated precise spike detection through both in vitro and in vivo acquisition of the neural signal. The prototype chip consumed 0.88 μW/channel at a 0.5-V supply for the recording and compressed about 89% of neural data, saving the power consumption and bandwidth in the system.