Ising Machines (IMs) provide a novel approach for solving combinatorial optimization problems efficiently. This paper investigates the practical implementation of CMOS oscillator-based IMs, focusing on two architectures: Duffing oscillator and pump-based parametric oscillator networks. Both architectures, scaled up to 5-node networks, have been designed at transistor-and behavioral-level, respectively, using a 180nm CMOS process. Simulation results show that the Duffing oscillator IM achieves 100% accuracy with convergence times of 2 to 4.5 mu s, while the pump-based parametric oscillator IM achieves 98% with convergence times of 10 to 15 mu s, when solving 5-node Max-Cut problems at 22 MHz. A comparative analysis reveals critical insights into the trade-offs between accuracy, complexity, and feasibility of these CMOS oscillator-based IMs.

This paper presents a low-noise bioimpedance (bio-Z) spectroscopy interface for electrical impedance myography (EIM) over the 1 kHz to 2 MHz frequency range. The proposed interface employs a sinusoidal signal generator based on direct-digital-synthesis (DDS) to improve the accuracy of the bio-Z reading, and a quadrature low-intermediate frequency (IF) readout to achieve a good noise-to-power efficiency and the required data throughput to detect muscle contractions. The readout is able to measure baseline and time-varying bio-Z by employing robust and power-efficient low-gain IAs and sixth-order single-bit bandpass (BP) ΔΣ ADCs. The proposed bio-Z spectroscopy interface is implemented in a 180 nm CMOS process, consumes 344.3 - 479.3 μ W, and occupies 5.4 mm 2 area. Measurement results show 0.7 mΩ/√Hz sensitivity at 15.625 kHz, 105.8 dB SNR within 4 Hz bandwidth, and a 146.5 dB figure-of-merit. Additionally, recording of EIM in time and frequency domain during contractions of the bicep brachii muscle demonstrates the potential of the proposed bio-Z interface for wearable EIM systems.

This paper presents a 16-channel analog frontend (AFE) for wearable multi-channel surface electromyography recording. The proposed architecture adopts frequency-division multiplexing (FDM), enabling extensive sharing of signal conditioning circuitry and requiring only three cables for transmission to an external back-end for digital signal processing. Benefiting from the up-conversion process, the FDM signal exhibits robustness against cable motion artifacts and mains interference, allowing short-distance communication without compromising signal quality. This work achieves a channel-to-cable ratio of 16:3, dramatically reducing system complexity. Implemented in a 180 nm CMOS technology, the proposed 16-channel AFE occupies only 6.42 mm2 and consumes 40.1 µW per channel from a 1.5 V supply. Measurements on a forearm demonstrate the capability to simultaneously detect muscle activation from various muscle groups, showcasing its potential for gesture recognition applications.

Neuromuscular electrical stimulation (NMES) is a self-directed home based therapeutic tool in early rehabilitation for musculoskeletal (MSK) conditions. However, the effectiveness of traditional NMES is fundamentally constrained by muscle fatigue. To address this limitation, this work proposes a detection system, which simultaneously records multifrequency electrical impedance myography (EIM) and surface electromyography(sEMG) in real time for time-frequency analysis of muscle activation, contraction, and fatigue. To demonstrate the ability to monitor these muscle physiological states, two experiments involving weightless and weighted dynamic contractions of the biceps brachii muscle were performed. Results from these experiments show synchronous changes in sEMG and EIM spectra during contractions, and clear trends in sEMG’s mean power frequency (MPF) and EIM spectra with fatigue progression. Additionally, the configurable 4-channel NMES has been electrically evaluated for clinical use, demonstrating the feasibility of the proposed system for closed-loop stimulation. This work showcases the potential of sEMG and multi-frequency EIM to enhance the effectiveness of NMES for MSK conditions by capturing the behavior of distinct mechanisms of muscle fatigue.

This paper presents a proof-of-concept analog Ising Machine, which can solve combinatorial optimization problems using bifurcations in networks of coupled Duffing oscillators. The proof-of-concept system consists of a network of four coupled Duffing oscillators implemented with low-cost components on a prototyping board. Experimental results demonstrate that the proposed prototype operates as an Ising Machine and it can solve various Max-Cut problems. This work provides the foundation towards realizing analog Ising Machines based on circuits that exhibit bifurcation properties, such as the Duffing oscillators, and that can be scaled to large networks.

The ability to perform accurate continuous glucose monitoring without blood sampling has revolutionised the management of diabetes. Newer methods that can allow measurements during longer periods are necessary to substantially improve patients’ quality of life. This paper presents an alternative method for glucose monitoring which is based on electrical impedance spectroscopy. A battery-less implantable bioimpedance spectroscope was designed, built, and used in an in vivo study on pigs. After a recovery period of 14 days post surgery, a total of 236 subcutaneous bioimpedance measurements obtained from intravenous glucose tolerance tests, with glucose concentration ranges between 77.4 and 523.8 mg/dL, were analyzed. The results show that glucose concentrations estimated by subcutaneous bioimpedance measurements correlate very well to the blood glucose reference values. The pigs were clinically healthy throughout the study, and the postmortem examinations revealed no signs of adverse effects related to the sensor. The implantation of the sensor requires minor surgery. The implant, being externally powered, could in principle last indefinitely. These encouraging results demonstrate the potential of the bioimpedance method to be used in future continuous glucose monitoring systems.

This brief presents an integrated solution to over-current protection in neuromuscular stimulators. The proposed approach provides fast detection of a single-fault condition, i.e., unintentional electrode short circuit or malfunction of the stimulator, thereby preventing prolonged high-intensity currents from flowing into tissues. In addition, a programmable current threshold enables the system to be also used for monitoring the stimulation intensity. The proposed solution was designed in a 180 nm high-voltage CMOS technology, and its functionality was verified by post-layout simulations in which the safety mechanisms were tested under fault conditions. The implementation only occupies an area of 0.286 mm2, making it feasible to be embedded in fully integrated NMES stimulators while providing the required patient safety.

This paper presents a low-distortion current-mode sinusoidal signal generator for bioimpedance spectroscopy measurements. The proposed full current-mode operation enables linearity enhancement and potential savings in silicon area and power consumption. Programmability in the low-pass filter and current driver enables impedance measurements from 0.2 Ω to10 kΩ over a wide frequency range from 1 kHz to 1 MHz.The current generator, designed in a 0.18 μm CMOS process, consumes between 736 μW at the lowest frequency and gain, and 1.70 mW at the highest frequency and gain, and occupies 1.76 mm² silicon area. Post-layout simulation results show a spurious-free dynamic range larger than 40 dBc over the entire frequency range, which enables bioimpedance measurements with errors below 1%, as it is required for wearable devices evaluating neuromuscular disorders.

This paper presents a high input impedance, low-noise, and low-distortion analog front-end (AFE) for bioimpedance (bio-Z) spectroscopy measurements targeting neuromuscular health assessments. The proposed 8-phase quadrature mixer-first architecture achieves a high input impedance through passive mixers driven by non-overlapping clocks. The 8-phase signals are recombined to extract the real and imaginary parts of the bio-Z, while rejecting unwanted harmonics to improve linearity. Programmability of the AFE enables accurate bio-Z measurements up to 10 kΩ for 11 logarithmically spaced frequencies, in the 1 kHz to 1 MHz frequency range. The AFE, designed in a 0.18 μm CMOS process, consumes 245.99 μW at the lowest gain and 300.56 μW at the highest gain, and occupies 2.4 mm2 silicon area. Post-layout simulation results show that the input impedance is always higher than the electrode impedance by more than 10x. The AFE achieves a sensitivity of 7.7 mΩrms, and a maximum SNDR of 103.87 dBFS over a 61 Hz bandwidth. These results demonstrate that the proposed AFE enables bio-Z measurements, using dry electrodes, with errors below 1%.

Ising Machines (IMs) have the potential to outperform conventional Von-Neuman architectures in notoriously difficult optimization problems. Various IM implementations have been proposed based on quantum, optical, digital and analog CMOS, as well as emerging technologies. Networks of coupled electronic oscillators have recently been shown to exhibit characteristics required for implementing IMs. However, for this approach to successfully solve complex optimization problems, a highly reconfigurable implementation is needed. In this work, the possibility of implementing highly reconfigurable oscillator-based IMs is explored. An implementation based on quasiperiodically modulated coupling strength through a common medium is proposed and its potential is demonstrated through numerical simulations. Moreover, a proof-of-concept implementation based on CMOS coupled ring oscillators is proposed and its functionality is demonstrated. Simulation results show that our proposed architecture can consistently find the Max-Cut solution and demonstrate the potential to greatly simplify the physical implementation of highly reconfigurable oscillator-based IMs.