Respiratory rate is an essential parameter in the clinical monitoring of hospital patients. It can be measured in various ways, such as by recording chest movements, breathing flow or heart rate variations. Current sensor technology allows the development of new kinds of convenient and portable respiratory rate recorders, including smart shirts, which enable more efficient healthcare processes in hospitals. This study carried out respiratory rate measurements using a sensor belt with a high-resolution accelerometer (capacitive MEMS) and an EMFit (electret film) pressure sensor. Results obtained from tests on 10 subjects showed that both sensors are feasible for respiratory rate measurement; the reliability of the MEMS was 90%, while that of the EMFit was 90-100%. In addition, the results showed that the location of the sensor module on the chest is important.

The one repetition maximum (1RM) is an important method to measure muscular strength. The purpose of this study was to evaluate a new method to predict 1RM bench press performance from a submaximal lift. The developed method was evaluated by using different load levels (50, 60, 70, 80, and 90% of 1RM). The subjects were active floorball players (n = 22). The new method is based on the assumption that the estimation of 1RM can be calculated from the submaximal weight and the maximum acceleration of the submaximal weight during the lift. The submaximal bench press lift was recorded with a 3-axis accelerometer integrated to a wrist equipment and a data acquisition card. The maximum acceleration was calculated from the measurement data of the sensor and analyzed in personal computer with LabView-based software. The estimated 1RM results were compared with traditionally measured 1RM results of the subjects. An own estimation equation was developed for each load level, that is, 5 different estimation equations have been used based on the measured 1RM values of the subjects. The mean (+/-SD) of measured 1RM result was 69.86 (+/-15.72) kg. The mean of estimated 1RM values were 69.85-69.97 kg. The correlations between measured and estimated 1RM results were high (0.89-0.97; p < 0.001). The differences between the methods were very small (-0.11 to 0.01 kg) and were not significantly different from each other. The results of this study showed promising prediction accuracy for estimating bench press performance by performing just a single submaximal bench press lift. The estimation accuracy is competitive with other known estimation methods, at least with the current study population.

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Abstract-The pressure distribution of the sole includes important information of gait during walking or running. For example, by monitoring the details ofpressure distributions in the sole in normal walking many malpositions of the foot can be easily detected. In this study a simple and versatile EMFI sensor based real-time pressure mapping system was developed for gait analysis purposes. The system consists ofa thin andflexible insole, including 16 tiny EMFI sensor elements, connected via a customized analog amplifier and digital data acquisition card to a PC computer. The PC-software of the measurement system shows the pressure in each small sensor element of the sole in real time, and records the data to a file. The accuracy and reliability of the system was preliminarily evaluated by experimental measurements. The results showed out that the system has capability to measure the pressure distributions of the foot sole reliably. The correlation coefficient between the applied pressure and the sensor output was 0,99. The next phase of the research project is to evaluate applicability of the system for evaluation ofgait with large number oftest subjects.