![]() A 100kΩ resistor was used between each of the push buttons and their respective Digital input. Two push buttons were soldered together between the power source and each to a Digital input of the data logger (pins D5 and D6). A switch button was placed between the power source and the two boards (i.e., data logger and accelerometer board) enabling us to start and stop powering the device manually. The battery was recharged using a charger for Lipo batteries (Micro Lipo-USB Lilon-Lipo Battery Charger – V1 Adafruit). The microcontroller board and the breakout sensor board were both powered by a single 3.7v LiPo rechargeable battery. The circuit design consists of the ATmega328 based data logger connected to a triple axis Analog accelerometer ADX元35 ( Fig. 3) that has a full sensing range of +/−3 g. We provide the circuit design as well as an exhaustive list of instructions to easily reproduce and modify our data logger. Nonetheless, virtually any kind of Analog signal can be used. As a simple, yet straightforward proof of concept, we collected data from a triple axis Analog accelerometer. We propose a low-cost portable device that harvests the capacities of a microcontroller in the recording of Analog data into a microSD card. A fast-sampling rate is particularly relevant when recording continuous events and is crucial when attempting to detect early onset of movement disorders. When it comes to data collection, whether it be in fundamental research or clinical diagnoses, the measuring precision is a critical factor that can drastically affect data resolution, hence the conclusion or diagnosis. Applications of microcontrollers in laboratories have already proved useful in neuroscience and related fields, for example in the building of low-cost operant chambers, or data loggers. These advantages come with a non-negligible requirement in time spent in developing new solutions and engineering background in electronics and programming. Microcontroller boards that recently became easily programmable via USB connection are a game changer for researchers, not only because they offer an affordable alternative to commercially available scientific equipment, but also because they allow for more flexibility. The counterpart is the narrow range of use they offer. Laboratory equipment are developed to meet specific demands and being easy to use. There is a need in the development of more sensitive and accessible physiological monitoring systems. ![]() Early stages of progressive, neurodegenerative movement disorders are generally associated with symptoms that are too mild and difficult to measure. Moreover, it can be customized to fit with a wide variety of applications in biomedical research by substituting the three-axial Analog accelerometer with virtually any type of Analog sensors or devices that output Analog signals.Īccurate and early detection of movement disorders is crucial yet challenging. Our wearable and fast-sampling rate data logger overcomes limits that we identified in previous studies, by being low-cost, capable of fast sampling rate, and easily replicated. A Fourier transform followed by a principal component analysis discriminated accurately between body motions of two participants and two types of movement recorded (walking VS running). As a straightforward proof-of-concept, we tested our device embedded with a three-axial Analog accelerometer and were able to record triple axis acceleration of body movements in high resolution. We provide data analysis instructions, including publicly available scripts to facilitate its replication and customization. We describe here the circuit design and an exhaustive list of instructions to build a small, lightweight, and fast sampling rate data logger (up to 5 kHz for simultaneous recording of 3 channels and up to 40 kHz when using a single channel). ![]() We propose a wearable, versatile, and open-source data logger that harvests the capacities of a low-cost microcontroller and enables fast-sampling recording of Analog signals into a microSD card.
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