New Approach of Cycling Phases Detection to Improve FES-Pedaling in SCI Individuals

Baptista, Roberto de Souza; Sijobert, Benot; Coste, Christine

doi:10.1109/iros.2018.8594162

Cited by 5 publications

(4 citation statements)

References 16 publications

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“…If other volunteers had participated in the experiment, the mechanical adjustments would have to be carried out individually, which would have demanded a relative effort to define the best FES pulse parametrization (i.e., the stimulation range of each angle). Studies have suggested the use of IMUs as a better approach for cycling phase detection, which could reduce this effort and improve FE -pedaling by SCI individuals [35][36][37].…”

Section: Discussionmentioning

confidence: 99%

Development of a High-Power Capacity Open Source Electrical Stimulation System to Enhance Research into FES-Assisted Devices: Validation of FES Cycling

Coelho-Magalhães

Fachin-Martins

Silva

et al. 2022

Sensors

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Since the first Cybathlon 2016, when twelve teams competed in the FES bike race, we have witnessed a global effort towards the development of stimulation and control strategies to improve FES-assisted devices, particularly for cycling, as a means to practice a recreational physical activity. As a result, a set of technical notes and research paved the way for many other studies and the potential behind FES-assisted cycling has been consolidated. However, engineering research needs instrumented devices to support novel developments and enable precise assessment. Therefore, some researchers struggle to develop their own FES-assisted devices or find it challenging to implement their instrumentation using commercial devices, which often limits the implementation of advanced control strategies and the possibility to connect different types of sensor. In this regard, we hypothesize that it would be advantageous for some researchers in our community to enjoy access to an entire open-source FES platform that allows different control strategies to be implemented, offers greater adaptability and power capacity than commercial devices, and can be used to assist different functional activities in addition to cycling. Hence, it appears to be of interest to make our proprietary electrical stimulation system an open-source device and to prove its capabilities by addressing all the aspects necessary to implement a FES cycling system. The high-power capacity stimulation device is based on a constant current topology that allows the creation of biphasic electrical pulses with amplitude, width, and frequency up to 150 mA, 1000 µs, and 100 Hz, respectively. A mobile application (Android) was developed to set and modify the stimulation parameters of up to eight stimulation channels. A proportional-integral controller was implemented for cadence tracking with the aim to improve the overall cycling performance. A volunteer with complete paraplegia participated in the functional testing of the system. He was able to cycle indoors for 45 min, accomplish distances of more than 5 km using a passive cycling trainer, and pedal 2400 m overground in 32 min. The results evidenced the capacity of our FES cycling system to be employed as a cycling tool for individuals with spinal cord injury. The methodological strategies used to improve FES efficiency suggest the possibility of maximizing pedaling duration through more advanced control techniques.

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Section: Discussionmentioning

confidence: 99%

Development of a High-Power Capacity Open Source Electrical Stimulation System to Enhance Research into FES-Assisted Devices: Validation of FES Cycling

Coelho-Magalhães

Fachin-Martins

Silva

et al. 2022

Sensors

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“…Conventionally, FES onset is determined by the crank position, which is measured by an encoder or an inertial measurement unit. Inertial measurement units can also be placed on the pilot's legs to directly measure the knee angle (38,44) or thigh inclination, indicating the knee flexion or extension phase (45,46), as input in the FES control system. Mechanomyography sensors have been used to monitor muscle activity in real time during stimulation and supervise muscle fatigue (47,48).…”

Section: Devices and Methodsmentioning

confidence: 99%

How the CYBATHLON Competition Has Advanced Assistive Technologies

Jaeger

Baptista

Basla

et al. 2023

Annu. Rev. Control Robot. Auton. Syst.

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Approximately 1.1. billion people worldwide live with some form of disability, and assistive technology has the potential to increase their overall quality of life. However, the end users’ perspective and needs are often not sufficiently considered during the development of this technology, leading to frustration and nonuse of existing devices. Since its first competition in 2016, CYBATHLON has aimed to drive innovation in the field of assistive technology by motivating teams to involve end users more actively in the development process and to tailor novel devices to their actual daily-life needs. Competition tasks therefore represent unsolved daily-life challenges for people with disabilities and serve the purpose of benchmarking the latest developments from research laboratories and companies from around the world. This review describes each of the competition disciplines, their contributions to assistive technology, and remaining challenges in the user-centered development of this technology.

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“…To address this, an approach that does not rely on a predefined geometrical model of the legs is required in order to automatically adapt stimulation timings to dynamic changes (e.g., seating position). In the last years, some research groups have proposed to replace the crank angle encoder with inertial measurement units (IMU) located on the user’s limbs [ 15 , 16 , 17 , 18 ]. Inertial measurement units placed on anatomical segments allow for generic and adaptive ways of defining the stimulation patterns based on leg movement criteria (i.e., maximum knee flexion/extension) [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

A Novel Framework for Quantifying Accuracy and Precision of Event Detection Algorithms in FES-Cycling

Guillou

Schmoll

Sijobert

et al. 2021

Sensors

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Functional electrical stimulation (FES) is a technique used in rehabilitation, allowing the recreation or facilitation of a movement or function, by electrically inducing the activation of targeted muscles. FES during cycling often uses activation patterns which are based on the crank angle of the pedals. Dynamic changes in their underlying predefined geometrical models (e.g., change in seating position) can lead to desynchronised contractions. Adaptive algorithms with a real-time interpretation of anatomical segments can avoid this and open new possibilities for the automatic design of stimulation patterns. However, their ability to accurately and precisely detect stimulation triggering events has to be evaluated in order to ensure their adaptability to real-case applications in various conditions. In this study, three algorithms (Hilbert, BSgonio, and Gait Cycle Index (GCI) Observer) were evaluated on passive cycling inertial data of six participants with spinal cord injury (SCI). For standardised comparison, a linear phase reference baseline was used to define target events (i.e., 10%, 40%, 60%, and 90% of the cycle’s progress). Limits of agreement (LoA) of ±10% of the cycle’s duration and Lin’s concordance correlation coefficient (CCC) were used to evaluate the accuracy and precision of the algorithm’s event detections. The delays in the detection were determined for each algorithm over 780 events. Analysis showed that the Hilbert and BSgonio algorithms validated the selected criteria (LoA: +5.17/−6.34% and +2.25/−2.51%, respectively), while the GCI Observer did not (LoA: +8.59/−27.89%). When evaluating control algorithms, it is paramount to define appropriate criteria in the context of the targeted practical application. To this end, normalising delays in event detection to the cycle’s duration enables the use of a criterion that stays invariable to changes in cadence. Lin’s CCC, comparing both linear correlation and strength of agreement between methods, also provides a reliable way of confirming comparisons between new control methods and an existing reference.

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New Approach of Cycling Phases Detection to Improve FES-Pedaling in SCI Individuals

Cited by 5 publications

References 16 publications

Development of a High-Power Capacity Open Source Electrical Stimulation System to Enhance Research into FES-Assisted Devices: Validation of FES Cycling

Development of a High-Power Capacity Open Source Electrical Stimulation System to Enhance Research into FES-Assisted Devices: Validation of FES Cycling

How the CYBATHLON Competition Has Advanced Assistive Technologies

A Novel Framework for Quantifying Accuracy and Precision of Event Detection Algorithms in FES-Cycling

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