A multi-point heart rate monitoring using a soft wearable system based on fiber optic technology

Early diagnosis can be crucial to limit both the mortality and economic burden of cardiovascular diseases. Recent developments have focused on the continuous monitoring of cardiac activity for a prompt diagnosis. Nowadays, wearable devices are gaining broad interest for a continuous monitoring of the heart rate (HR). One of the most promising methods to estimate HR is the seismocardiography (SCG) which allows to record the thoracic vibrations with high non-invasiveness in out-of-laboratory settings. Despite significant progress on SCG, the current state-of-the-art lacks both information on standardized sensor positioning and optimization of wearables design. Here, we introduce a soft wearable system (SWS), whose novel design, based on a soft polymer matrix embedding an array of fiber Bragg gratings, provides a good adhesion to the body and enables the simultaneous recording of SCG signals from multiple measuring sites. The feasibility assessment on healthy volunteers revealed that the SWS is a suitable wearable solution for HR monitoring and its performance in HR estimation is strongly influenced by sensor positioning and improved by a multi-sensor configuration. These promising characteristics open the possibility of using the SWS in monitoring patients with cardiac pathologies in clinical (e.g., during cardiac magnetic resonance procedures) and everyday life settings.

Effects of Positioning of Multi-Sensor Devices on Occupancy and Indoor Environmental Monitoring in Single-Occupant Offices

The advancements in sensor and communication technologies drive the rapid developments in the applications of occupancy and indoor environmental monitoring in buildings. Currently, the installation standards for sensors are scarce and the recommendations for sensor positionings are very general. However, inadequate sensor positioning might diminish the reliability of sensor data, which could have serious impacts on the intended applications such as the performance of demand-controlled HVAC systems and their energy use. Thus, there is a need to understand how sensor positioning may affect the sensor data, specifically when using multi-sensor devices in which several sensors are being bundled together. This study is based on the data collected from 18 multi-sensor devices installed in three single-occupant offices (six sensors in each office). Each multi-sensor device included sensors to measure passive infrared (PIR) radiation, temperature, CO2, humidity, and illuminance. The results show that the positions of PIR and CO2 sensors significantly affect the reliability of occupancy detection. The typical approach of positioning the sensors on the ceiling, in the middle of offices, may lead to relatively unreliable data. In this case, the PIR sensor in that position has only 60% accuracy of presence detection. Installing the sensors under office desks could increase the accuracy of presence detection to 84%. These two sensor positions are highlighted in sensor fusion analysis as they could reach the highest accuracy compared to other pairs of PIR sensors. Moreover, sensor positioning can affect various indoor environmental parameters, especially temperature and illuminance measurements.

Optimal sensor positioning on pressurized equipment based on Value of Information

In this work, we apply a simulation-based framework that makes use of the Value of Information (VoI) for identifying the optimal spatial positioning of sensors on pressurized equipment. VoI is a utility-based Figure of Merit (FoM) which quantifies the benefits/losses of acquiring information. Sensors are typically positioned on pressurized equipment in line with specific recommendations based on operational experience, like UNI 11096 in Italy. We show that the recommendations in UNI 11096 are, indeed, justified and that, incidentally, relying on VoI for the optimization of the sensor positioning, one can achieve the same monitoring performance, as measured by VoI, where following UNI 11096, but with a reduced number of sensors. The proposed VoI-based approach can, thus, be used to confirm or revise recommendations coming from operational experience.

Which factors influence the accuracy of knee ROM data of the BPMpathway e-rehabilitation system? A concurrent validity study with healthy subjects

Aims and Objectives: As the population in different countries ages, there is an expected increase in the demand for TKA procedures in the coming decades. This increasing demand will face the healthcare systems and health care providers with new challenges. After TKA physiotherapy and exercise lead to short term improvements in physical function. Physiotherapy exercise provided at home is an appealing approach with the possibility of wider acceptability and uptake in the near future. E-rehabilitation or telerehabilitation are the terms used to define medical rehabilitation programs that are implemented at home with the use of information and communication technologies (ICT). The BPMpathway (270 Vision Ltd., Andover, UK) is an internet home-based biofeedback and remote patient monitoring system. The system comprises a single high-performance wearable wireless sensor, a patient application that can be downloaded for free and a software application for the clinic. The aim of the present study was to test the concurrent validity of the ROM data displayed by the BPMpathway system for knee exercises. Materials and Methods: This is a concurrent validity study conducted in a laboratory setting. The ROM data obtained with the BPMpathway system was compared with the ROM data acquired simultaneously with a twin-axis digital goniometer (BIOPAC Systems, Inc., California USA). The effects of sensor positioning (position of the sensor on the limb) and ergonomic factors (chair height) on ROM were investigated. The sample consisted of healthy male subjects with different body compositions. The data acquisition was carried out in both systems at a sample rate of 100Hz. Data was analyzed with MATLAB. The Root Mean Squared Error (RMSE) was used to calculate the difference between the values measured by the two devices. Additionally the mean ± SD values for each system were plotted and the absolute difference of the mean curves was plotted as measurement error. A ROM mean difference of 5° between both systems was considered as clinically irrelevant. Results: A 20% increase or reduction in sitting height led to a RMSE increase. A ventral shift of the BPMpathway sensor by 45° and 90° caused significant measurement errors. A vertical shift was associated with a diminution of the measurement errors. The lowest RMSE (2.4°) was achieved when the sensor was placed directly below the knee. The effects of the manipulations were similar for all subjects. RMSE values were higher in subject A, which had a high body mass index (BMI). Conclusion: The knee ROM data measured by the BPMpathway system seems reliable and comparable to the data of the concurrent system used in this investigation, provided the instructions of the manufacturer are respected concerning the sitting position of the subject for knee exercises, and disregarding the same instructions for sensor positioning, by placing the sensor directly below the knee. Changes in seating position and rotation shifts of the sensor induced measurement errors.

Sensor Positioning Influences the Accuracy of Knee Rom Data of an E-Rehabilitation System: A Preliminary Study with Healthy Subjects

E-rehabilitation is the term used to define medical rehabilitation programs that are implemented at home with the use of information and communication technologies. The aim was to test whether sensor position and the sitting position of the patient influence the accuracy of knee range of movement (ROM) data displayed by the BPMpathway e-rehabilitation system. A preliminary study was conducted in a laboratory setting with healthy adults. Knee ROM data was measured with the BPMpathway e-rehabilitation system and simultaneously with a BIOPAC twin-axis digital goniometer. The main outcome was the root mean squared error (RMSE). A 20% increase or reduction in sitting height led to a RMSE increase. A ventral shift of the BPMpathway sensor by 45° and 90° caused significant measurement errors. A vertical shift was associated with a diminution of the measurement errors. The lowest RMSE (2.4°) was achieved when the sensor was placed below the knee. The knee ROM data measured by the BPMpathway system is comparable to the data of the concurrent system, provided the instructions of the manufacturer are respected concerning the sitting position of the subject for knee exercises, and disregarding the same instructions for sensor positioning, by placing the sensor directly below the knee.