Bioimedical pilot projects e.g., telemedicine, homecare, animal and human trials usually involve several physiological measurements. Technical development of these projects is time consuming and in particular costly. A versatile but affordable biosignal measurement platform can help to reduce time and risk while keeping the focus on the important goal and making an efficient use of resources. In this work, an affordable and open source platform for development of physiological signals is proposed. As a first step an 8–12 leads electrocardiogram (ECG) and respiration monitoring system is developed. Chips based on iCoupler technology have been used to achieve electrical isolation as required by IEC 60601 for patient safety. The result shows the potential of this platform as a base for prototyping compact, affordable, and medically safe measurement systems. Further work involves both hardware and software development to develop modules. These modules may require development of front-ends for other biosignals or just collect data wirelessly from different devices e.g., blood pressure, weight, bioimpedance spectrum, blood glucose, e.g., through Bluetooth. All design and development documents, files and source codes will be available for non-commercial use through project website, BiosignalPI.org.
This paper presents a smartphone-based platform for large-scale, low-cost, long-term naturalistic data collection aimed at vulnerable road users (VRUs). The approach taken is to collect naturalistic movement data from VRUs based on information from the embedded sensors in high-end smartphones. The Smartphone application, LogYard, developed in the current study, allows the recording of high quality data (tri-axial acceleration and rotation at 100 Hz plus GPS position and velocity each second). This way, large data quantities from ATV drivers’ movements during daily use in different use cases, can be transferred from a large number of users and accumulated in a cloud-based server for off-line analysis.
Apart from the description on how data is recorded and managed in the smartphone-based platform, also a procedure on how to include participants to studies and how private integrity issues and informed consent can be handled from a distance is presented.
By means of the presented smartphone based platform, large number of participants taking part in several parallel on-going studies can be easily administered. This makes the platform a powerful tool to use in large-scale, low-cost, long-term studies providing data from large groups of study participants.
The information made available this way can be used to develop automatic crash notification (ACN) systems directed to VRUs based on identifying movements outside what is “normal” for bicyclists, mopedists, motorcyclists and ATV users.