Search Results (6)

The study aimed at obtaining a precise view of the modification of heart rate variability (HRV) and respiratory rate with the help of “smart clothes” (the Hexoskin Smart Shirt, Hexoskin Smart Sensors & AI, Montreal, QC, Canada) during a 45 min session of “dry” immersion (DI), which is considered a model of Earth-based weightlessness. Eight healthy subjects aged 19 to 21 years participated in the study. Hexoskin Smart Shirt provided a .wav sound file. For analysis, the ecg_peaks function of the neurokit2 library was applied. HRV parameters were calculated within 5 min segments with the help of the pyHRV toolbox. Time-domain (HR and SDNN) and frequency-domain (HF, LF, and VLF) HRV parameters, sample, and approximate entropy were calculated. Thus, the “smart cloth” technology appears as a reliable telemetric instrument to monitor cardiac and respiratory regulation during the DI session. Full article

Physiological stress in healthy subjects was assessed using heart rate (HR), monitored with the help of Hexoskin smart garments. HRs were collected during daily life activities and in laboratory settings during stress tests. Heart rate variability parameters were computed and referenced with expert levels of stress. The data were processed with the help of machine learning algorithms (Random Forest, CatBoost, XGB, LGBM, SVR). The Random Forest Regressor provided the best rate of correct entries (86%), and the CatBoost Regressor provided the shortest time (2 ms) for the assessment of stress levels. Full article

Background: Limited research has been done to measure ambulatory respiratory behavior, in particular those associated with tobacco use, in the natural environment due to a lack of monitoring techniques. Respiratory topography parameters provide useful information for modeling particle deposition in the lung and assessing exposure risk and health effects associated with tobacco use. Commercially available Wearable Respiratory Monitors (WRM), such as the Hexoskin Smart Garment, have embedded sensors that measure chest motion and may be adapted for measuring ambulatory lung volume. Methods: Self-reported “everyday” and “some days” Hookah and Cigarette smokers were recruited for a 3-day natural environment observation study. Participants wore the Hexoskin shirt while using their preferred tobacco product. The shirt was calibrated on them prior to, during, and after the observation period. A novel method for calculating the calibration parameters is presented. Results: N_H = 5 Hookah and N_C = 3 Cigarette participants were enrolled. Calibration parameters were obtained and applied to the observed chest motion waveform from each participant to obtain their lung volume waveform. Respiratory topography parameters were derived from the lung volume waveform. Conclusion: The feasibility of using the Hexoskin for measuring ambulatory respiratory topography parameters in the natural environment is demonstrated. Full article

Background: Natural environment inhalation topography provides useful information for toxicant exposure, risk assessment and cardiopulmonary performance. Commercially available wearable respiratory monitors (WRMs), which are currently used to measure a variety of physiological parameters such as heart rate and breathing frequency, can be leveraged to obtain inhalation topography, yet little work has been done. This paper assesses the feasibility of adapting these WRMs for measuring inhalation topography. Methods: Commercially available WRMs were compiled and assessed for the ability to report chest motion, data analysis software features, ambulatory observation capabilities, participant acceptability, purchasing constraints and affordability. Results: The following WRMs were found: LifeShirt, Equivital EQ02 LifeMonitor, Smartex WWS, Hexoskin Smart Garment, Zephyr BioHarness, Nox T3&A1, BioRadio, SleepSense Inductance Band, and ezRIP & zRIP Durabelt. None of the WRMs satisfied all six assessment criteria in a manner enabling them to be used for inhalation topography without modification and development. Conclusions: The results indicate that there are WRMs with core technologies and characteristics that can be built upon for ambulatory inhalation topography measurement in the NE. Full article

Sleep quality has been directly linked to cognitive function, quality of life, and a variety of serious diseases across many clinical domains. Standard methods for assessing sleep involve overnight studies in hospital settings, which are uncomfortable, expensive, not representative of real sleep, and difficult to conduct on a large scale. Recently, numerous commercial digital devices have been developed that record physiological data, such as movement, heart rate, and respiratory rate, which can act as a proxy for sleep quality in lieu of standard electroencephalogram recording equipment. The sleep-related output metrics from these devices include sleep staging and total sleep duration and are derived via proprietary algorithms that utilize a variety of these physiological recordings. Each device company makes different claims of accuracy and measures different features of sleep quality, and it is still unknown how well these devices correlate with one another and perform in a research setting. In this pilot study of 21 participants, we investigated whether sleep metric outputs from self-reported sleep metrics (SRSMs) and four sensors, specifically Fitbit Surge (a smart watch), Withings Aura (a sensor pad that is placed under a mattress), Hexoskin (a smart shirt), and Oura Ring (a smart ring), were related to known cognitive and psychological metrics, including the n-back test and Pittsburgh Sleep Quality Index (PSQI). We analyzed correlation between multiple device-related sleep metrics. Furthermore, we investigated relationships between these sleep metrics and cognitive scores across different timepoints and SRSM through univariate linear regressions. We found that correlations for sleep metrics between the devices across the sleep cycle were almost uniformly low, but still significant (p < 0.05). For cognitive scores, we found the Withings latency was statistically significant for afternoon and evening timepoints at p = 0.016 and p = 0.013. We did not find any significant associations between SRSMs and PSQI or cognitive scores. Additionally, Oura Ring’s total sleep duration and efficiency in relation to the PSQI measure was statistically significant at p = 0.004 and p = 0.033, respectively. These findings can hopefully be used to guide future sensor-based sleep research. Full article

Current medical facilities usually lead to a very high cost especially for developing countries, rural areas and mass casualty incidents. Therefore, advanced electronic health systems are gaining momentum. In this paper, we first compared our novel off the shelf experimental wired Body Sensor Networks (BSN), that is, Digital First Aid (DigiAID) with the existing commercial product called as Hexoskin. We showed the viability of DigiAID through extensive real measurements during daily activities by both male and females. It was found that the major hurdle was wires to be worn by the subjects. Accordingly, we proposed and characterized the wireless DigiAID platform for wireless BSN (WBSN). Understanding the effect of body movements on wireless data transmission in WBSN is also of major importance. Therefore, this paper comprehensively evaluates and analyzes the impact of body movements, (a) to ensure transmission of data at different radio power levels and (b) its impact on the topology of the WBSN. Based on this we have proposed a dynamic power control algorithm that adapts the transmitting power according to the packet reception in an energy efficient manner. The results show that we have achieved substantial power savings at various nodes attached to the human body. Full article