IEEE transactions on biomedical circuits and systems最新文献

In this work, a biphasic and bipolar current-controlled stimulator with high loading adaptability is proposed. The stimulator consisted of an on-chip high voltage generator, output driver and an 8-bit current DAC (Digital-to-Analog Converter), can constantly provide the required stimulus currents ranging from 0.1mA to a maximum of 20mA, as the loading impedance varied within 0.5kΩ - 5kΩ. With a nearly 12 V output voltage, the overstress and reliability issues of the circuits are thoroughly considered and carefully addressed in this work. To achieve high loading impedance adaptability, this paper proposes a novel PAM (Pulse Amplitude Modulation) loop control architecture to drive the charge pump (CP), which provides a significantly higher output dynamic range compared to conventional methods such as PFM (Pulse Frequency Modulation) and PSM (Pulse Skip Modulation). In addition, to further improve the Power Conversion Efficiency (PCE) of the high voltage generator, a new technique, PAM-based Dual-Domain Voltage Scaling (PAM-DDVS), is proposed to minimize unnecessary energy consumption while achieving high adaptive range. The fully-integrated stimulus chip with 2 output channels is fabricated in TSMC 0.18μm 1.8V/3.3V process, and occupies a core die area of approximately 1.6 mm². Imitation tests are conducted to validate the functionality of the stimulus chip.

Three-dimensional (3D) cell culture is gaining attention for its ability to better mimic tissue environments in vitro, enhancing drug screening efficiency. Tracking biological dynamics in such a setup requires advanced monitoring technologies. This paper presents a miniature magnetic resonance imaging (MRI) platform tailored for imaging 3D cell-culture morphology within a microliter-volume microwell, enabling real-time and on-site visualization of biological dynamics. The system utilizes an MRI application-specific integrated circuit for excitation and detection of the nuclear magnetic resonance (NMR) signal. To cope with the small-volume sensing, the platform features a customized frontend probe, which includes a miniaturized saddle coil and a PDMS-molded sample well for in-situ microliter sample containment and detection. Our proof-of-concept measurements on samples demonstrate an MRI image resolution of 90×128×88 $rm mu m$^³, along with continuous, multi-perspective (transverse and longitudinal) imaging of 3D cultures, including spheroid slice visualization. These results highlight the system's applicability and potential for future biological analysis and drug screening, offering researchers a valuable tool for advancing in vitro studies.

Surface-bound electrochemical aptamer-based (E-AB) sensors are a promising approach for continuous in-vivo and in-vitro biomolecular monitoring because they offer high selectivity, sensitivity, and real-time detection. However, accurately co-simulating E-AB sensors with readout circuits remains challenging due to the redox reporter's position-dependent electron-transfer kinetics and the electrical double layer's (EDL) complex behavior at the electrode-electrolyte interface. Here, we present a compact, SPICE-compatible electrochemical cell model that combines a Verilog-A implementation of the Marcus-Hush-based electron-transfer (ET) kinetics with a fractional-order RC-ladder representation of the EDL's non-ideal capacitance. The conventional Butler-Volmer model is replaced by Marcus-Hush kinetics, which features bounded and quantum mechanically derived ET rate constants, improving not only the model's physical interpretability but also numerical stability in circuit simulations. The model was validated with two E-AB sensors using square-wave voltammetry (SWV) across a range of excitation frequencies and target concentrations to confirm that the simulated transient currents accurately capture ET kinetics, thermodynamics, and the Langmuir isotherm's concentration response. When co-simulated with a transimpedance amplifier constructed with the TI OPA4354, the model produced electronic noise spectra that more closely matched experimental data, when compared with spectra simulated using the simplified Randles circuit model. These results demonstrate that the proposed model provides a physically grounded framework for simulating surface-bound redox-based electrochemical biosensors and enables accurate co-simulation with readout circuits.