[Precise measurement of human heart rate based on multi-channel radar data fusion].

To achieve non-contact measurement of human heart rate and improve its accuracy, this paper proposes a method for measuring human heart rate based on multi-channel radar data fusion. The radar data were firstly extracted by human body position identification, phase extraction and unwinding, phase difference, band-pass filtering optimized by power spectrum entropy, and fast independent component analysis for each channel data. After overlaying and fusing the four-channel data, the heartbeat signal was separated using frost-optimized variational modal decomposition. Finally, a chirp Z-transform was introduced for heart rate estimation. After validation with 40 sets of data, the average root mean square error of the proposed method was 2.35 beats per minute, with an average error rate of 2.39%, a Pearson correlation coefficient of 0.97, a confidence interval of [-4.78, 4.78] beats per minute, and a consistency error of -0.04. The experimental results show that the proposed measurement method performs well in terms of accuracy, correlation, and consistency, enabling precise measurement of human heart rate.

Sensor-Integrated Chairs for Lower Body Strength and Endurance Assessment.

This paper describes an automated method and device to conduct the Chair Stand Tests of the Fullerton Functional Test Battery. The Fullerton Functional Test is a suite of physical tests designed to assess the physical fitness of older adults. The Chair Stand Tests, which include the Five Times Sit-to-Stand Test (5xSST) and the 30 Second Sit-to-Stand Test (30CST), are the standard for measuring lower-body strength in older adults. However, these tests are performed manually, which can be labor-intensive and prone to error. We developed a sensor-integrated chair that automatically captures the dynamic weight and distribution on the chair. The collected time series weight-sensor data is automatically uploaded for immediate determination of the sit-to-stand timing and counts, as well as providing a record for future comparison of lower-body strength progression. The automatic test administration can provide significant labor savings for medical personnel and deliver much more accurate data. Data from 10 patients showed good agreement between the manually collected and sensor-collected 30CST data (M = 0.5, SD = 1.58, 95% CI = 1.13). Additional data processing will be able to yield measurements of fatigue and balance and evaluate the mechanisms of failed standing attempts.

A Multi-Channel Borehole Strain Measurement and Acquisition System Based on FPGA.

In this study, an FPGA(Field Programmable Gate Array)-based borehole strain measurement system was designed that makes extensive use of digital signal processing operations to replace analog circuits. Through the formidable operational capability of FPGA, the sampled data were filtered and denoised to improve the signal-to-noise ratios. Then, with the goal of not reducing observational accuracy, the signal amplification circuit was removed, the excitation voltage was reduced, and the dynamic range of the primary adjustments was expanded to 130 dB. The system's online compilation function made it more flexible to changes in measurement parameters, allowing it to adapt to various needs. In addition, the efficiency of the equipment use was enhanced. The actual observational results showed that this study's FPGA-based borehole strain measurement system had a voltage resolution higher than 1 µV. Clear solid tides were successfully recorded in low-frequency bands, and seismic wave strain was accurately recorded in high-frequency bands. The arrival times and seismic phases of the seismic waves S and P were clearly recorded, which met the requirements for geophysical field deformation observations. Therefore, the system proposed in this study is of major significance for future analyses of geophysical and crust deformation observations.

MADV-DAQ: Multi-channel Arduino-based differential voltage data acquisition system for remote strain measurement applications.

Wind turbine power generation, both onshore and offshore, has gained significant popularity over the past few decades. However, the design of a turbine's foundation, capable of supporting a tall structure subject to large horizontal forces, remains challenging. Complex wind loading and intricate soil-structure interaction between the foundation and the supporting soil requires consideration. Although commercial structural health monitoring (SHM) systems provide several advantages, they remain cost prohibitive. This paper demonstrates the development, testing, fabrication, installation and validation of a low-cost, multi-channel, Arduino-based differential voltage data acquisition system (MADV-DAQ) suitable for remote, battery powered measurements of multiple Wheatstone bridge-based (strain) sensors. The instrumented wind turbine (120 m high, 3.45 MW generation capacity) forms part of a newly constructed onshore wind farm in South Africa. The developed MADV-DAQ system proved valuable in measuring strains associated with the wind turbine tower, quantifying the true magnitude of the loads being transferred to the underlying foundation. MADV-DAQ was designed to relay the real-time measurements to two, independent cloud platforms for aggregation, visualization and subsequent analysis. MADV-DAQ was purposefully designed as a universal data acquisition system, compatible with any Wheatstone bridge-based sensor design, including strain gauges, tensiometer and similar MEMS-based sensors.