0.6 V, 116 nW Neural Spike Acquisition IC with Self-Biased Instrumentation Amplifier and Analog Spike Extraction.

This paper presents an ultralow power 0.6 V 116 nW neural spike acquisition integrated circuit with analog spike extraction. To reduce power consumption, an ultralow power self-biased current-balanced instrumentation amplifier (IA) is proposed. The passive RC lowpass filter in the amplifier acts as both DC servo loop and self-bias circuit. The spike detector, based on an analog nonlinear energy operator consisting of a low-voltage open-loop differentiator and an open-loop gate-bulk input multiplier, is designed to emphasize the high frequency spike components nonlinearly. To reduce the spike detection error, the adjacent spike merger is also proposed. The proposed circuit achieves a low IA current consumption of 46.4 nA at 0.6 V, noise efficiency factor (NEF) of 1.81, the bandwidth from 102 Hz to 1.94 kHz, the input referred noise of 9.37 µVrms, and overall power consumption of 116 nW at 0.6 V. The proposed circuit can be used in the ultralow power spike pulses acquisition applications, including the neurofeedback systems on peripheral nerves with low neuron density.

Micro Bio Processor Development Kit for Wireless Neural Implants.

Micro Bio Processor version 1.5 (MBPv15) Development Kit is specially engineered to support various function-alities of implantable devices such as bio-signal sensing, neural stimulation, and dual-band wireless connectivity & charging. It provides a convenient way to evaluate the MBPv15 chip solution as a system component by a modular design of hardware and software. As a result, MBPv15 chip solution enables to develop wireless neural implants in a mm-scale form factor with ultra-low power consumption by achieving 1.6 mW for neural spike detection and 9.8 mW for neural stimulation, respectively.

A 10 nV/rt Hz noise level 32-channel neural impedance sensing ASIC for local activation imaging on nerve section.

A 10 nV/rt Hz noise level 32-channel neural impedance sensing ASIC is presented for the application of local activation imaging in nerve section. It is increasingly known that the monitoring and control of nerve signals can improve physical and mental health. Major nerves, such as the vagus nerve and the sciatic nerve, consist of a bundle of fascicles. Therefore, to accurately control a particular application without any side effects, we need to know exactly which fascicle was activated. The only way to find locally activated fascicle is to use electrical impedance tomography (EIT). The ASIC to be introduced is designed for neural EIT applications. A neural impedance sensing ASIC was implemented using CMOS 180-nm process technology. The integrated input referred noise was calculated to be 0.46 µVrms (noise floor 10.3 nVrms/rt Hz) in the measured noise spectrum. At an input of 80 mV, the squared correlation coefficient for linear regression was 0.99998. The amplification gain uniformity of 32 channels was in the range of + 0.23% and - 0.29%. Using the resistor phantom, the simplest model of nerve, it was verified that a single readout channel could detect a signal-to- noise ratio of 75.6 dB or more. Through the reservoir phantom, real-time EIT images were reconstructed at a rate of 8.3 frames per second. The developed ASIC has been applied to in vivo experiments with rat sciatic nerves, and signal processing is currently underway to obtain activated nerve cross-sectional images. The developed ASIC was also applied to in-vivo experiments with rat sciatic nerves, and signal processing is currently underway to obtain locally activated nerve cross-sectional images.

A 160 µA biopotential acquisition IC with fully integrated IA and motion artifact suppression.

This paper proposes a 3-channel biopotential monitoring ASIC with simultaneous electrode-tissue impedance measurements which allows real-time estimation of motion artifacts on each channel using an an external µC. The ASIC features a high performance instrumentation amplifier with fully integrated sub-Hz HPF rejecting rail-to-rail electrode-offset voltages. Each readout channel further has a programmable gain amplifier and programmable 4th order low-pass filter. Time-multiplexed 12 b SAR-ADCs are used to convert all the analog data to digital. The ASIC achieves >; 115 dB of CMRR (at 50/60 Hz), a high input impedance of >; 1 GΩ and low noise (1.3 µVrms in 100 Hz). Unlike traditional methods, the ASIC is capable of actual motion artifact suppression in the analog domain before final amplification. The complete ASIC core operates from 1.2 V with 2 V digital IOs and consumes 200 µW when all 3 channels are active.

Effect of pressurization methods on the accuracy of wrist blood pressure measurement.

In developing a wrist blood pressure monitor of high and reliable accuracy, the effect of different pressurization methods on the accuracy of blood pressure measurement at the wrist using oscillometry is investigated in this paper. 30 volunteers are recruited and blood pressure readings are taken with three different methods of pressurizing the wrist. It was found that measurement of mean arterial pressure (MAP) is more accurate when the wrist is locally compressed directly over the radial artery (-2.6 ± 11.4 mmHg) or with a region of surrounding tissue (10.3 ± 6.0 mmHg) than when the whole wrist is compressed by a conventional, constricting cuff (-11.4 ± 16.4 mmHg). Characteristics of accuracy, however, differ between the two local pressurization methods. While a square airbag that compresses the wrist directly over the radial artery may measure the most accurate MAP on average, the range of errors among individuals is large. Contrarily, measurements taken by pressurizing a region over the radial artery with a bladder are least affected by individual variability. In order to measure blood pressure accurately at the wrist while unbiased by the population-based algorithmic compensation to ensure accuracy among different individuals, therefore, the use of local pressurization method may be the most appropriate.

Factors affecting the accuracy of volume-oscillometric blood pressure measurement during partial pressurization of the wrist.

We compared the volume-oscillometric responses of the airbag pressure sensor and the contact force sensor across and along the radial artery on the wrist during partial pressurization by an airbag. Because of the anatomic structure and non-uniform pressurization pressure distribution, elongated and shifted oscillometric pressure waveform envelope variations are observed. For the contact force sensors directly above the radial artery, S-shaped pressurization curves can be seen possibly due to temporal softening of the radial artery stiffness at near zero transmural pressure. These differences in the shape of oscillometric envelope as well as pressurization curve may be the leading factors for inaccuracies of volume-oscillometric blood pressure measurement by partial pressurization method using an airbag.

The preliminary study on the clinical application of the WHAM (Wearable Heart Activity Monitor).

In this paper, we investigated the validity of the WHAM (wearable heart activity monitor) in the clinical applications, which has been implemented as a wearable ambulatory device for continuously and long-term monitoring user's cardiac conditions. To this end, using the WHAM and the conventional Holter monitor the ECG signals over 24 hours were recorded during daily activities. The signal from the WHAM was compared with that from the conventional Holter monitor in terms of the readability of the signal, the quality of the signal, and the accuracy of arrhythmia detection. The performance of the WHAM was a little lower as compared with the conventional Holter monitor, although showing no significant difference (the readability of the signal: 97.2% vs 99.3%; the quality of the signal: 0.97 vs 0.98; the accuracy of arrhythmia detection: 96.2% vs 98.1%). From these results, it is likely that the WHAM shows the performance enough to be used in the clinical application as a wearable ambulatory monitoring device.