Wireless medical sensor measurements of fatigue in patients with multiple sclerosis

Comparative Analysis of Supervised Classifiers for the Evaluation of Sarcopenia Using a sEMG-Based Platform

Sarcopenia is a geriatric condition characterized by a loss of strength and muscle mass, with a high impact on health status, functional independence and quality of life in older adults. To reduce the effects of the disease, just the diagnostic is not enough, it is necessary more than recognition. Surface electromyography is becoming increasingly relevant for the prevention and diagnosis of sarcopenia, also due to a wide diffusion of smart and minimally invasive wearable devices suitable for electromyographic monitoring. The purpose of this work is manifold. The first aim is the design and implementation of a hardware/software platform. It is based on the elaboration of surface electromyographic signals extracted from the Gastrocnemius Lateralis and Tibialis Anterior muscles, useful to analyze the strength of the muscles with the purpose of distinguishing three different “confidence” levels of sarcopenia. The second aim is to compare the efficiency of state of the art supervised classifiers in the evaluation of sarcopenia. The experimentation stage was performed on an “augmented” dataset starting from data acquired from 32 patients. The latter were distributed in an unbalanced manner on 3 “confidence” levels of sarcopenia. The obtained results in terms of classification accuracy demonstrated the ability of the proposed platform to distinguish different sarcopenia “confidence” levels, with highest accuracy value given by Support Vector Machine classifier, outperforming the other classifiers by an average of 7.7%.

Assessment of Residual Radioactivity by a Comprehensive Wireless, Wearable Device in Thyroid Cancer Patients Undergoing Radionuclide Therapy and Comparison With the Results of a Home Device: A Feasibility Study

Objective: To investigate the feasibility of using a wireless wearable device (WD) in differentiated thyroid cancer (DTC) patients undergoing radionuclide therapy with I-131 (RAI) and protected hospitalization, this study compared the measurements of residual radioactivity obtained with those registered by a permanent environmental home device (HD). Methods: Twenty consecutive patients undergoing RAI hospitalized in restricted, controlled areas were enrolled. The patients underwent comprehensive monitoring of vital/nonvital parameters. We obtained 45580± 13 measurements from the WD, detecting the residual radioactivity for each patient during approximately 56 hours of hospitalization, collecting data 53 times per hour. The samples, collected during daily activities, were averaged every two hours, and the results correlated with those from the HD. Bland-Altman analysis was also used to evaluate the agreement between the two techniques. Results: A significant relationship between the WD and HD was observed (r = 0.96, p < 0.0001). Bland-Altman analysis recognized the agreement between measurements by the WD and HD. The mean value at the end of the first day of hospitalization was 80.81 microSv/h and 60.77 microSv/h (p = ns for WD and HD), whereas those at the end of the second day were 47.08 and 24.96 (p = ns). In the generalized linear model (GLM), a similar trend in performance across time was found with the two techniques. Conclusion: This study demonstrates good agreement between the residual radioactivity measures estimated by the WD and HD modalities, rendering them interchangeable. This approach will allow both the optimization of medical staff exposure and safer patient discharge. Abbreviations: wireless device (WD); differentiated thyroid cancer (DTC); radionuclide therapy with I-131 (RAI); home device (HD); generalized linear model (GLM).

A wireless sEMG recording system and its application to muscle fatigue detection

Surface electromyography (sEMG) is an important measurement for monitoring exercise and fitness. Because if its high sampling frequency requirement, wireless transmission of sEMG data is a challenge. In this article a wireless sEMG measurement system with a sampling frequency of 2 KHz is developed based upon a MSP 430 microcontroller and Bluetooth transmission. Standard isotonic and isometric muscle contraction are clearly represented in the receiving user interface. Muscle fatigue detection is an important application of sEMG. Traditional muscle fatigue is detected from the median frequency of the sEMG power spectrum. The regression slope of the linear regression of median frequency is an important muscle fatigue index. A more negative slope value represents a higher muscle fatigue condition. To test the system performance, muscle fatigue detection was examined by having subjects run on a pedaled-multifunctional elliptical trainer for approximately 30 minutes at three loading levels. Ten subjects underwent a total of 60 exercise sessions to provide the experimental data. Results showed that the regression slope gradually decreases as expected, and there is a significant gender difference.