Scalable ECG hardware and algorithms for extended runtime of wearable sensors

Abstract

Everything in nature tries to reach the lowest possible energy level. Therefore any natural or artificial system must have the ability to adjust itself to the changing requirements of its surrounding environment. In this paper we address this issue by an ECG sensor designed to be adjustable during runtime, having the ability to reduce the power consumption at cost of the informational content. Accessible for everyone, standard ECG hardware and open source software has been used to realize an ECG processing system for wearable applications. The average power consumption has been measured for each mode of operation. Finally we take conclusion to conciser context-aware scaling as key feature to address the energy issue of wearable sensor systems

Internet of Medical Things: A Review of Recent Contributions Dealing With Cyber-Physical Systems in Medicine

“…Banerjee The robustness and security challenges have been described independently from the modeling perspective only once with the use of smart algorithm selection for biosignal acquisition robustness improvement [64]. Verification and validation have been considered separately from any modeling aspects in the very specific situation where an implementation already existed, with the real life testing of CPS devices such as an ECG sensor [65] or a general CPS hardware node [66].…”

ECG Acquisition Based AVR Microcontroller and Java Application for Visualisation via Email Service

“…Given that SD card latency considered for a buffer of 512 Bytes when writing in our SD card is about 1ms, we should understand the need of a parallel computing, when aquiring data since we have to store them, as they are collected . FreeRTOS was used as a real-time operating system (RTOS) to set timers, handle events and tasks, and to avoid wasting SD Card latency [18], the Error! Reference source not found.…”

“…153-158 III. EXPERIMENTAL TESTS, RESULTS AND DISCUSSION The first part is the electronic circuit built around the AVR atmega328 on the board Nano of the Arduino project which is cheaper than PIC microcontrollers used in [9] [8], to acquire heart's electrical activity through the Single Lead board of SparkFun with the AD8232 [18] instead of traditional AD620, and INA118 [9], where a (RTOS) Real Time Operating Systems is embedded, for sampling accurately at 1024 microsecond time interval as datalogger that is about 970 Sa/s (Sample per second), accurately better than [9] which is 310Hz. Those digital data are saved in an SD card, which are then uploaded via email as attachment, and sent to the clinic care email address.…”

Towards a comprehensive power consumption model for wireless sensor nodes

“…Several detailed studies are presented by Tobola et al in which they compare different microcontrollers for WSNs [4], quantify the impact of different sampling rates for various algorithms [5], and optimize the hard-and software implementation of an ECG sensor [6]. Likewise, Berlin et al [7] increased the runtime of a wearable data logger by varying the sampling rates, the low-power modes, the type of used SD-card and by applying a run length encoding.…”