Abstract
One of the objectives of the medicine is to modify patients’ ways of living. In this context, a key role is played by the diagnosis. When dealing with acquisition systems consisting of multiple wireless devices located in different parts of the body, it becomes fundamental to ensure synchronization between the individual units. This task is truly a challenge, so one aims to limit the complexity of the calculation and ensure long periods of operation. In fact, in the absence of synchronization, it is impossible to relate all the measurements coming from the different subsystems on a single time scale for the extraction of complex characteristics. In this paper, we first analyze in detail all the possible causes that lead to have a system that is not synchronous and therefore not usable. Then, we propose a firmware implementation strategy and a simple but effective protocol that guarantees perfect synchrony between the devices while keeping computational complexity low. The employed network has a star topology with a master/slave architecture. In this paper a new approach to the synchronization problem is introduced to guarantee a precise but not necessarily accurate synchronization between the units. In order to demonstrate the effectiveness of the proposed solution, a platform consisting of two different types of units has been designed and built. In particular, a nine Degrees of Freedom (DoF) Inertial Measurement Unit (IMU) is used in one unit while a nine-DoF IMU and all circuits for the analysis of the superficial Electromyography (sEMG) are present on the other unit. The system is completed by an Android app that acts as a user interface for starting and stopping the logging operations. The paper experimentally demonstrates that the proposed solution overcomes all the limits set out and it guarantees perfect synchronization of the single measurement, even during long-duration acquisitions. In fact, a less than 30 μ s time mismatch has been registered for a 24 h test, and the possibility to perform complex post-processing on the acquired data with a simple and effective system has been proven.
Highlights
In many areas of research, medicine, and sport it is important to collect data on particular parameters concerning a subject to obtain information on his/her health condition
The reference broadcast synchronization (RBS) algorithm proposed in [24] offers a solution in which the leader sends a broadcast message to all the nodes
Two simple actions allow one to reach the goal: the first, to put the writing on micro SD card at a low priority, favoring the real-time clock (RTC) and the communication with the Inertial Measurement Unit (IMU); the second, to prefer burst writing, correctly sizing the vectors to store in the RAM for the temporary storage of the values coming from the IMU or sensors in general while writing on the micro SD card
Summary
In many areas of research, medicine, and sport it is important to collect data on particular parameters concerning a subject to obtain information on his/her health condition. Advanced forms of PD involve the possibility for the patient to alternate phases in which motor muscles are operative (ON) to phases in which they stop to work (OFF) [9] This can be related to an ineffective or changed drug therapy and only platforms for long-term monitoring of the patient can be helpful for identifying these types of issues. A better solution seems to be represented by offline processing, in which every mote saves the results of its surveys on a persistent memory and after gathering the data from the whole set of units the data collection is processed This final step calls for the BAN coordinator to be in charge of strict time synchronization between all motes.
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