Abnormalities in cardiac function arise irregularly and typically involve multimodal electrical, mechanical vibrations, and acoustics alterations. This paper proposes an Electro-Mechano-Acoustic (EMA) activity model for mapping the complete macroscopic cardiac function to refine the systematic interpretation of cardiac multimodal assessment. We abstract this activity pattern and build the mapping system by analyzing the functional comparison of the heart pump and Electronic Fuel Injection (EFI) system from the multimodal characteristics of the heart. Electrocardiogram (ECG), seismocardiogram (SCG) & Ultra-Low Frequency seismocardiogram (ULF-SCG), and Phonocardiogram (PCG) are selected to implement the EMA mapping respectively. First, a novel low-frequency cardiograph compound sensor capable of extracting both SCG and ULF-SCG is proposed, which is integrated with ECG and PCG modules on a single hardware device for portable dynamic acquisition. Afterward, a multimodal signal processing chain further analyses the acquired synchronized signals, and the extracted ULF-SCG is shown to indicate changes in heart volume. In particular, the proposed method based on waveform curvature is used to extract 9 feature points of the SCG signal, and the overall recognition accuracy reaches over 90% in the data collected by EMA portable device. Ultimately, we integrate the portable device and signal processing chains to form the EMA cardiovascular mapping system (EMACMS). As a next-generation system solution for cardiac daily dynamic monitoring, which can map the mechanical coupling and electromechanical coupling process, extract multi-characteristic heart rate variability (HRV), and enable extraction of important time intervals of cardiac activity to assess cardiac function.

This brief presents an energy-efficient continuous-time incremental delta-sigma modulator (CT IDSM), where the first integrator employs a fourth-order feedforward-compensated amplifier based on an AC-coupled OTA-stacking amplifier (AC-OSA) and utilizes a charge neutralization reset scheme (CNRS). Extending the AC-OSA to incremental structures significantly improves the energy efficiency of the ADC. The core innovation is the use of CNRS for periodic resets, addressing common-mode (CM) disturbances and incomplete differential-mode (DM) signal resets caused by the conventional shorted integration capacitor scheme. Additionally, to enhance area and power efficiency when using high-tap FIR DACs in CT IDSMs, we propose an excess-loop-delay compensation (ELDC) FIR DAC suitable for single-bit (SB) architectures. A third-order single-loop SB CT IDSM with an eight-tap FIR DAC is fabricated in a 65nm CMOS process and achieves SNDR, SNR, and DR values of 81.5dB, 81.8dB, and 85dB, respectively at a Nyquist conversion rate of 200kS/s. The core area is 0.227mm2, and the ADC consumes 275μW. The Schreier (SNDR) figure-of-merit (FoM) is 167.1dB.

Transcutaneous electrical nerve stimulation (TENS) is constrained by high skin impedance and unstable electrode contact. This study proposes a novel composite electrode system comprising a polyvinyl alcohol/silver (PVA/Ag) microneedle array and a highly conductive polyacrylamide/lithium chloride (PAAm/LiCl) hydrogel. The PVA/Ag microneedles (~365 µm in height, ~48 µm tip diameter) possess sufficient mechanical strength to penetrate the stratum corneum, establishing a low-resistance pathway. The complementary PAAm/LiCl hydrogel exhibits high conductivity (10.28 S/m) and mechanical flexibility, further optimizing the interface contact. The experimental results demonstrate that this composite system achieves low electrochemical impedance and induces stable, clear electromyographic responses in vivo. It effectively addresses the common issues of electrode detachment and signal attenuation associated with conventional electrodes, offering a promising hardware solution for efficient and comfortable wearable rehabilitation devices.

Auscultation of the chest is a fundamental diagnostic tool for cardiovascular and pulmonary diseases. However, the two main chest sound parts, heart sound (HS) and lung sound (LS), are often mixed, limiting diagnostic accuracy. This paper presents a novel Phase-Enhanced Neural Network (PENN) for HS and LS separation. To address the under-utilization of phase information, PENN integrates a feedforward connection that feeds the input spectrum into the Restorer, enabling phase recovery based on the local inference feature of phase. A time-frequency Dual-Path Transformer (DPT) is employed to expand the network's receptive field and enhance performance. To interpret the effectiveness of PENN, two new metrics, mSI-SDRi and pSI-SDRi, are proposed to separately evaluate the contributions of magnitude and phase. Experiments show that PENN achieves pSI-SDRi improvements of 1.44 dB for HS and 2.25 dB for LS under a LS cutoff frequency ($f_{c\text{lung}}$) of 60Hz. Extensive experimental results demonstrate the effectiveness and robustness of PENN, offering a promising solution to improve the accuracy of auscultation.

Transcutaneous electrical stimulation (TES) is a non-invasive technique that delivers electrical currents through the skin to modulate peripheral neural and muscular activity. However, conventional surface stimulation often exhibits limited spatial selectivity because current spreads across superficial and deep tissues. To investigate physical principles that may inform future transcutaneous applications without assuming anatomical or physiological fidelity, this study developed a finite-element framework based on an idealized multilayer cylindrical limb model. The model represented skin, adipose tissue, muscle, cortical bone, and bone marrow using concentric tissue domains parameterized with averaged forearm dimensions and literature-derived electrical properties. Two-dimensional and three-dimensional surface-electrode montages were evaluated by varying return-electrode positions, axial electrode spacing, and inter-channel current ratios. The simulations showed that electrode configuration influenced the location, volume, and compactness of high-maximum-envelope-modulation-amplitude (MEMA) regions. Within the investigated idealized geometry, intermediate return-electrode angles (approximately θ₂ = 130–150°) produced more centrally distributed intramuscular high-MEMA regions, whereas current-ratio modulation shifted the MEMA_max-defined field maximum under fixed electrodes. These results demonstrate the computational feasibility of regulating TI electric-field distributions in a controlled virtual model rather than physiological selectivity or clinical efficacy. Translation to actual transcutaneous stimulation will require staged validation using anatomically realistic models, physical phantoms, physiological experiments, and ultimately human studies.

Acupuncture, a key therapeutic method in traditional Chinese medicine (TCM), has been widely adopted in various clinical fields. Quantitative research on acupuncture manipulation parameters is critical for achieving standardized techniques. However, quantitative mechanical detection of acupuncture parameters remains limited. In this study, a kinematic and dynamic model of acupuncture is established, and key parameters such as the lifting-thrusting force, acceleration, velocity, and displacement, as well as the twirling-rotating angular velocity and angle, are identified. To measure these critical parameters, we propose a quantitative system comprising a sensing needle equipped with a force sensor and an inertial measurement unit (IMU), as well as an external camera module to capture image information. By fusing visual and IMU data, we can accurately identify the stationary or motion states of the needle, enabling segmented computation of the lifting-thrusting velocity and displacement. The experimental results demonstrate that the sensing needle achieves comprehensive detection with high precision, featuring an accuracy of 0.45% in force measurement and an RMSE of 1.2 mm in displacement. The extracted parameters provide an objective description of the operational characteristics and motion patterns of the four basic acupuncture manipulations and two auxiliary manipulations. These findings provide valuable tools and methods for research on acupuncture standardization.