Design of an Arduino-based platform interfaced by Bluetooth low energy with Myo armband for controlling an under-actuated transradial prosthesis

Gaetani, Federico; Zappatore, Giovanni Antonio; Visconti, Paolo; Primiceri, Patrizio

doi:10.1109/icicdt.2018.8399787

Cited by 10 publications

(5 citation statements)

References 1 publication

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“…The armband operation is managed by ARM Cortex M4 processor while data transmission is performed by BLE NRF51822 chip toward the HM-11 BLE module mounted on bottom side of the prosthesis control unit. Myo armband is shown disassembled in Figure 1 (b)and its control board in Figure 1 (c) [4]; two lithium batteries are located into two elements and recharged providing 5V voltage by micro-USB connector. Different research studies were conducted on Myo armband suitability for prosthesis and virtual reality applications; in [5] it was used with the aim to control PeopleBot robot for reaching bio-infected or radioactive environments or for helping disabled people.…”

Section: Introductionmentioning

confidence: 99%

A prosthetic limb managed by sensors-based electronic system: Experimental results on amputees

Gaetani¹,

Fazio

Zappatore³

et al. 2020

Bulletin EEI

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Taking the advantages offered by smart high-performance electronic devices, transradial prosthesis for upper-limb amputees was developed and tested. It is equipped with sensing devices and actuators allowing hand movements; myoelectric signals are detected by Myo armband with 8 ElectroMyoGraphic (EMG) electrodes, a 9-axis Inertial Measurement Unit (IMU) and Bluetooth Low Energy (BLE) module. All data are received through HM-11 BLE transceiver by Arduino board which processes them and drives actuators. Raspberry Pi board controls a touchscreen display, providing user a feedback related to prosthesis functioning and sends EMG and IMU data, gathered via the armband, to cloud platform thus allowing orthopedic during rehabilitation period, to monitor users’ improvements in real time. A GUI software integrating a machine learning algorithm was implemented for recognizing flexion/extension/rest gestures of user fingers. The algorithm performances were tested on 9 male subjects (8 able-bodied and 1 subject affected by upper-limb amelia), demonstrating high accuracy and fast responses.

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Section: Introductionmentioning

confidence: 99%

A prosthetic limb managed by sensors-based electronic system: Experimental results on amputees

Gaetani¹,

Fazio

Zappatore³

et al. 2020

Bulletin EEI

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“…We have shown that our sensor can be used to measure sEMG signals and that these can be wirelessly submitted to a computer on which gesture classification can be conducted. Wireless, Bluetooth-controlled prosthetic arms have been demonstrated in the literature [ 30 ]. Hence, it would be possible to control such an arm using a wireless connection from our sensor to a computer and a simultaneous wireless connection from a computer to such a prosthesis.…”

Section: Discussionmentioning

confidence: 99%

A Circular, Wireless Surface-Electromyography Array

Deprez,

De Baecke,

Tijskens

et al. 2024

Sensors

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Commercial, high-tech upper limb prostheses offer a lot of functionality and are equipped with high-grade control mechanisms. However, they are relatively expensive and are not accessible to the majority of amputees. Therefore, more affordable, accessible, open-source, and 3D-printable alternatives are being developed. A commonly proposed approach to control these prostheses is to use bio-potentials generated by skeletal muscles, which can be measured using surface electromyography (sEMG). However, this control mechanism either lacks accuracy when a single sEMG sensor is used or involves the use of wires to connect to an array of multiple nodes, which hinders patients’ movements. In order to mitigate these issues, we have developed a circular, wireless s-EMG array that is able to collect sEMG potentials on an array of electrodes that can be spread (not) uniformly around the circumference of a patient’s arm. The modular sEMG system is combined with a Bluetooth Low Energy System on Chip, motion sensors, and a battery. We have benchmarked this system with a commercial, wired, state-of-the-art alternative and found an r = 0.98 (p < 0.01) Spearman correlation between the root-mean-squared (RMS) amplitude of sEMG measurements measured by both devices for the same set of 20 reference gestures, demonstrating that the system is accurate in measuring sEMG. Additionally, we have demonstrated that the RMS amplitudes of sEMG measurements between the different nodes within the array are uncorrelated, indicating that they contain independent information that can be used for higher accuracy in gesture recognition. We show this by training a random forest classifier that can distinguish between 6 gestures with an accuracy of 97%. This work is important for a large and growing group of amputees whose quality of life could be improved using this technology.

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“…By performing built-in MYO gestures, it is possible to achieve total accuracy of between 50% and 97% (tested by three subjects without previous training) [5]. The contribution of EMG is also visible in a transradial myoelectric prostheses [6]. The most advanced solution controlled by sEMG includes dexterous hand prosthesis.…”

Section: Related Workmentioning

confidence: 99%

Gesture Interaction in the Lirkis Cave Based on Emg and Kinect Sensor

Pastornicky¹,

Chovanec²

2020

AEI

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The article deals with the possibilities of interaction in the virtual environment (VE) of the CAVE LIRKIS system. Commonly available peripherals are keyboard, mouse or gamepad. However, these do not provide a sufficient level of immersion, such as hand gestures. The MYO armband has proven to be one of the potential devices for improving interaction. Therefore, a system for editing an object transformation in VE was created using hand gestures and movements. Enhancing the natural user interface (NUI) of the system with additional interaction capabilities has proven the device to be suitable also for further development.

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Design of an Arduino-based platform interfaced by Bluetooth low energy with Myo armband for controlling an under-actuated transradial prosthesis

Cited by 10 publications

References 1 publication

A prosthetic limb managed by sensors-based electronic system: Experimental results on amputees

A prosthetic limb managed by sensors-based electronic system: Experimental results on amputees

A Circular, Wireless Surface-Electromyography Array

Gesture Interaction in the Lirkis Cave Based on Emg and Kinect Sensor

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