The Piezo-resistive MC Sensor is a Fast and Accurate Sensor for the Measurement of Mechanical Muscle Activity

Silver Nanowire-Based Flexible Strain Sensor for Human Motion Detection

Accurately capturing human movements is a crucial element of health status monitoring and a necessary precondition for realizing future virtual reality/augmented reality applications. Flexible motion sensors with exceptional sensitivity are capable of detecting physical activities by converting them into resistance fluctuations. Silver nanowires (AgNWs) have become a preferred choice for the development of various types of sensors due to their outstanding electrical conductivity, transparency, and flexibility within polymer composites. Herein, we present the design and fabrication of a flexible strain sensor based on silver nanowires. Suitable substrate materials were selected, and the sensor's sensitivity and fatigue properties were characterized and tested, with the sensor maintaining reliability after 5000 deformation cycles. Different sensors were prepared by controlling the concentration of silver nanowires to achieve the collection of motion signals from various parts of the human body. Additionally, we explored potential applications of these sensors in fields such as health monitoring and virtual reality. In summary, this work integrated the acquisition of different human motion signals, demonstrating great potential for future multifunctional wearable electronic devices.

Preliminary study of reliability of transcutaneous sensors in measuring intraabdominal pressure

Early recognition of elevated intraabdominal pressure (IAP) in critically ill patients is essential, since it can result in abdominal compartment syndrome, which is a life-threatening condition. The measurement of intravesical pressure is currently considered the gold standard for IAP assessment. Alternative methods have been proposed, where IAP assessment is based on measuring abdominal wall tension, which reflects the pressure in the abdominal cavity. The aim of this study was to evaluate the feasibility of using patch-like transcutaneous sensors to estimate changes in IAP, which could facilitate the monitoring of IAP in clinical practice. This study was performed with 30 patients during early postoperative care. All patients still had an indwelling urinary catheter postoperatively. Four wearable sensors were attached to the outer surface of the abdominal region to detect the changes in abdominal wall tension. Additionally, surface EMG was used to monitor the activity of the abdominal muscles. The thickness of the subcutaneous tissue was measured with ultrasound. Patients performed 4 cycles of the Valsalva manoeuvre, with a resting period in between (the minimal resting period was 30 s, with a prolongation as necessary to ensure that the fluid level in the measuring system had equilibrated). The IAP was estimated with intravesical pressure measurements during all resting periods and all Valsalva manoeuvres, while the sensors continuously measured changes in abdominal wall tension. The association between the subcutaneous thickness and tension changes on the surface and the intraabdominal pressure was statistically significant, but a large part of the variability was explained by individual patient factors. As a consequence, the predictions of IAP using transcutaneous sensors were not biased, but they were quite variable. The specificity of detecting intraabdominal pressure of 20 mmHg and above is 88%, with an NPV of 96%, while its sensitivity and PPV are currently far lower. There are inherent limitations of the chosen preliminary study design that directly caused the low sensitivity of our method as well as the poor agreement with the gold standard method; in spite of that, we have shown that these sensors have the potential to be used to monitor intraabdominal pressure. We are planning a study that would more closely resemble the intended clinical use and expect it to show more consistent results with a far smaller error.

Influence of sensor mass and adipose tissue on the mechanomyography signal of elbow flexor muscles

Mechanomyography (MMG) is a non-invasive technique that records muscle contraction using sensors positioned on the skin's surface. Therefore, it can have its signal attenuated due to the adipose tissue, directly influencing the results. This study evaluates the influence of different mass added to a sensor's assembly and the adipose tissue on MMG signals of elbow flexor muscles. Test protocol consisted of skinfold thickness measurement of 22 volunteers, followed by applying 2-3 s electrical stimulation for muscle contraction during the acquisition of MMG signals. MMG signals were processed in the time domain, using the average of the absolute amplitude, and expressed in gravity values (G), termed here as MMG(G). Tests occurred four times with different sensor masses. MMG data were processed and analyzed statistically using Friedman and Kruskal-Wallis tests to determine the differences between the MMG signals measured with different sensor masses. The Mann-Whitney analysis indicated differences in the MMG signals between groups with different skinfold thickness. MMG(G) signals suffered attenuation with increasing sensor mass (0.4416 G to 0.94 g; 0.3902 G to 2.64 g; 0.3762 G to 5.44 g; 0.3762 G to 7.14 g) and adipose tissue.

Electrically Elicited Force Response Characteristics of Forearm Extensor Muscles for Electrical Muscle Stimulation-Based Haptic Rendering

A haptic interface based on electrical muscle stimulation (EMS) has huge potential in terms of usability and applicability compared with conventional haptic interfaces. This study analyzed the force response characteristics of forearm extensor muscles for EMS-based haptic rendering. We introduced a simplified mathematical model of the force response, which has been developed in the field of rehabilitation, and experimentally validated its feasibility for haptic applications. Two important features of the force response, namely the peak force and response time, with respect to the frequency and amplitude of the electrical stimulation were identified by investigating the experimental force response of the forearm extensor muscles. An exponential function was proposed to estimate the peak force with respect to the frequency and amplitude, and it was verified by comparing with the measured peak force. The response time characteristics were also examined with respect to the frequency and amplitude. A frequency-dependent tendency, i.e., an increase in response time with increasing frequency, was observed, whereas there was no correlation with the amplitude. The analysis of the force response characteristics with the application of the proposed force response model may help enhance the fidelity of EMS-based haptic rendering.