OIDA: An optimal interval detection algorithm for automatized determination of stimulation patterns for FES-Cycling in individuals with SCI.

BACKGROUND: FES-Cycling is an exciting recreational activity, which allows certain individuals after spinal cord injury or stroke to exercise their paralyzed muscles. The key for a successful application is to activate the right muscles at the right time. METHODS: While a stimulation pattern is usually determined empirically, we propose an approach using the torque feedback provided by a commercially available crank power-meter installed on a standard trike modified for FES-Cycling. By analysing the difference between active (with stimulation) and passive (without stimulation) torques along a full pedalling cycle, it is possible to differentiate between contributing and resisting phases for a particular muscle group. In this article we present an algorithm for the detection of optimal stimulation intervals and demonstrate its functionality, bilaterally for the quadriceps and hamstring muscles, in one subject with complete SCI on a home trainer. Stimulation patterns were automatically determined for two sensor input modalities: the crank-angle and a normalized thigh-angle (i.e. cycling phase, measured via inertial measurement units). In contrast to previous studies detecting automatic stimulation intervals on motorised ergo-cycles, our approach does not rely on a constant angular velocity provided by a motor, thus being applicable to the domain of mobile FES-Cycling. RESULTS: The algorithm was successfully able to identify stimulation intervals, individually for the subject's left and right quadriceps and hamstring muscles. Smooth cycling was achieved without further adaptation, for both input signals (i.e. crank-angle and normalized thigh-angle). CONCLUSION: The automatic determination of stimulation patterns, on basis of the positive net-torque generated during electrical stimulation, can help to reduce the duration of the initial fitting phase and to improve the quality of pedalling during a FES-Cycling session. In contrast to previous works, the presented algorithm does not rely on a constant angular velocity and thus can be effectively implemented into mobile FES-Cycling systems. As each muscle or muscle group is assessed individually, our algorithm can be used to evaluate the efficiency of novel electrode configurations and thus could promote increased performances during FES-Cycling.

Benefits of 1-Yr Home Training With Functional Electrical Stimulation Cycling in Paraplegia During COVID-19 Crisis.

ABSTRACT: The purpose of this observational study was to report the experience of a 1-yr home training with functional electrical stimulation cycling of a person with T4 American Impairment Scale A paraplegia for 9 yrs, homebound due to the COVID-19 health crisis. The 40-yr-old participant had a three-phase training: V1, isometric stimulation; V2, functional electrical stimulation cycling for 3 sessions/wk; and V3, functional electrical stimulation cycling for 2-4 sessions/wk. Data on general and physical tolerance, health impact, and performance were collected. Borg Scale score relating to fatigue was 10.1 before training and 11.8 after training. The average score for satisfaction at the end of sessions was 8.7. Lean leg mass increased more than 29%, although total bone mineral density dropped by 1.6%. The ventilatory thresholds increased from 19.5 to 29% and the maximum ventilatory peak increased by 9.5%. Rosenberg's Self-esteem Scale score returned to its highest level by the end of training. For the only track event on a competition bike, the pilot covered a distance of 1607.8 m in 17 mins 49 secs. When functional electrical stimulation cycling training is based on a clear and structured protocol, it offers the person with paraplegia the opportunity to practice this activity recreationally and athletically. In times of crisis, this training has proven to be very relevant.

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

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.

Standardizing fatigue-resistance testing during electrical stimulation of paralysed human quadriceps muscles, a practical approach.

BACKGROUND: Rapid onset of muscular fatigue is still one of the main issues of functional electrical stimulation (FES). A promising technique, known as distributed stimulation, aims to activate sub-units of a muscle at a lower stimulation frequency to increase fatigue-resistance. Besides a general agreement on the beneficial effects, the great heterogeneity of evaluation techniques, raises the demand for a standardized method to better reflect the requirements of a practical application. METHODS: This study investigated the fatigue-development of 6 paralysed quadriceps muscles over the course of 180 dynamic contractions, evaluating different electrode-configurations (conventional and distributed stimulation). For a standardized comparison, fatigue-testing was performed at 40% of the peak-torque during a maximal evoked contraction (MEC). Further, we assessed the isometric torque for each electrode-configuration at different knee-extension-angles (70°-170°, 10° steps). RESULTS: Our results showed no significant difference in the fatigue-index for any of the tested electrode-configurations, compared to conventional-stimulation. We conjecture that the positive effects of distributed stimulation become less pronounced at higher stimulation amplitudes. The isometric torque produced at different knee-extension angles was similar for most electrode-configurations. Maximal torque-production was found at 130°-140° knee-extension-angle, which correlates with the maximal knee-flexion-angles during running. CONCLUSION: In most practical applications, FES is intended to initiate dynamic movements. Therefore, it is crucial to assess fatigue-resistance by using dynamic contractions. Reporting the relationship between produced torque and knee-extension-angle can help to observe the stability of a chosen electrode-configuration for a targeted range-of-motion. Additionally, we suggest to perform fatigue testing at higher forces (e.g. 40% of the maximal evoked torque) in pre-trained subjects with SCI to better reflect the practical demands of FES-applications.

FES-Induced Cycling in Complete SCI: A Simpler Control Method Based on Inertial Sensors.

This article introduces a novel approach for a functional electrical stimulation (FES) controller intended for FES-induced cycling based on inertial measurement units (IMUs). This study aims at simplifying the design of electrical stimulation timing patterns while providing a method that can be adapted to different users and devices. In most of studies and commercial devices, the crank angle is used as an input to trigger stimulation onset. We propose instead to use thigh inclination as the reference information to build stimulation timing patterns. The tilting angles of both thighs are estimated from one inertial sensor located above each knee. An IF-THEN rule algorithm detects, online and automatically, the thigh peak angles in order to start and stop the stimulation of quadriceps muscles, depending on these events. One participant with complete paraplegia was included and was able to propel a recumbent trike using the proposed approach after a very short setting time. This new modality opens the way for a simpler and user-friendly method to automatically design FES-induced cycling stimulation patterns, adapted to clinical use, for multiple bike geometries and user morphologies.