Jakub Parak

ABSTRACT In this contribution, a device for long term measurement of heart rate is described. The device is created based on development kit STM32-Primer2. Heart rate frequency is calculated from selected electrocardiograph lead from the external module. The device allows simultaneous recoding of acceleration which makes is appropriate for physical activity detection of the test subject. The recorded data is saved on a memory card as signals in raw form, which can be used for subsequent processing in various research areas. Modular solution is suitable for connection of other modules. This device is designed for research and educational purposes in the field of medical devices and signal processing.

ABSTRACT This paper presents a modular development telemonitoring system. The system consists of wireless communication and biosignal acquisition modules. These modules are connected to a control unit via an extension board. The control unit is based on STM32 EVO Primer development kit. An integrated accelerometer is used for monitoring of subject's activity. The system features a signal processing and heart rate frequency computing algorithm. A memory card is used for saving the heart rate frequency. A heart arrhythmia alarm and an activity monitor are implemented in the system as well. The system has a simple alarm and a signal visualization program for PC. The modular solution is suitable for other biosignals acquisition and for miscellaneous means of wireless data transfer. The system provides raw signal data for further signal processing. This system was designed mainly for development, research and educational purposes in telemonitoring systems.

Heart rate variability (HRV) provides significant information about the health status of an individual. Optical heart rate monitoring is a comfortable alternative to ECG based heart rate monitoring. However, most available optical heart rate monitoring devices do not supply beat-to-beat detection accuracy required by proper HRV analysis. We evaluate the beat-to-beat detection accuracy of a recent wrist-worn optical heart rate monitoring device, PulseOn (PO). Ten subjects (8 male and 2 female; 35.9±10.3 years old) participated in the study. HRV was recorded with PO and Firstbeat Bodyguard 2 (BG2) device, which was used as an ECG based reference. HRV was recorded during sleep. As compared to BG2, PO detected on average 99.57% of the heartbeats (0.43% of beats missed) and had 0.72% extra beat detection rate, with 5.94 ms mean absolute error (MAE) in beat-to-beat intervals (RRI) as compared to the ECG based RRI BG2. Mean RMSSD difference between PO and BG2 derived HRV was 3.1 ms. Therefore, PO provides an accurate method for long term HRV monitoring during sleep.

ABSTRACT Novel health monitoring devices and applications allow consumers easy and ubiquitous ways to monitor their health status. However, technologies from different providers lack both technical and semantic interoperability and hence the resulting health data is often deeply tied to specific service, which is limiting its re-usability and utilization in different services. We have designed a Wellness Warehouse Engine (W2E) that bridges this gap and enables seamless exchange of data between different services. W2E provides interfaces to various data sources and makes data available via unified REST API to other services. Importantly, it includes Unifier - an engine that allows transforming input data into generic units reusable by other services, and Analyzer - an engine that allows advanced analysis of input data, such as combining different data sources into new output parameters. In this paper, we describe the architecture of W2E and demonstrate its applicability by using it for uniting data from several consumer activity trackers. Finally, we discuss challenges of building Unifier and Analyzer engines for ever-enlarging number of new devices.

ABSTRACT This paper presents a modular development telemonitoring system. The system consists of wireless communication and biosignal acquisition modules. These modules are connected to a control unit via an extension board. The control unit is based on STM32 EVO Primer development kit. An integrated accelerometer is used for monitoring of subject's activity. The system features a signal processing and heart rate frequency computing algorithm. A memory card is used for saving the heart rate frequency. A heart arrhythmia alarm and an activity monitor are implemented in the system as well. The system has a simple alarm and a signal visualization program for PC. The modular solution is suitable for other biosignals acquisition and for miscellaneous means of wireless data transfer. The system provides raw signal data for further signal processing. This system was designed mainly for development, research and educational purposes in telemonitoring systems.

Digital signal processing and data analysis are very often used methods in a biomedical engineering research. This paper describes utilization of digital signal filtering on electrocardiogram (ECG). Designed filters are focused on removing supply network 50 Hz frequency and breathing muscle artefacts. Moreover, this paper contains description of three heart rate frequency detection algorithms from ECG. Algorithms are based on statistical and differential mathematical methods. All of the methods are compared on stress test measurements. All described methods are suitable for next simple implementation to a microprocessor for real-time signal processing and analysing.