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Objectives: This study was conducted to investigate the effects of combined progressive resistance training (PRT) and functional electrical stimulation-evoked leg cycling exercise (FES-LCE) on isometric peak torque and muscle volume in individuals with incomplete spinal cord injury. Patients and methods: In the single-blind, randomized controlled trial performed between April 2015 and August 2016, 28 participants were randomized between two exercise interventions (FES-LCE+PRT and FES-LCE alone), and training was conducted over 12 weeks. The isometric muscle peak torque and muscle volume for both lower limbs were measured at the baseline and after 6 and 12 weeks. Linear mixed-model analysis of variance was performed to test the effects of FES-LCE+PRT versus FES-LCE on each outcome measure over time via an intention-to-treat analysis. Results: Twenty-three participants (18 males, 5 females; mean age: 33.4±9.7 years; range 21 to 50 years) completed study (10 in the FES-LCE+PRT group, and 13 in the FES-LCE group). The 12-week pre-and posttraining change for left hamstrings’ muscle peak torque in the FES-LCE+PRT group (mean difference=4.5±7.9 Nm, 45% change, p Conclusion: The combination of PRT and FES-LCE was better in improving lower limb muscle strength and volume in chronic incomplete individuals with spinal cord injury.

In this paper, a cutting-edge method for creating control interfaces for intention detection in active transfemoral prosthetic devices is presented. Given the current trend in the prosthetics industry, a review of the literature over the last two decades has found a number of control algorithms utilized for intention detection implementation. Scientific publications, books, and online resources were evaluated for published material on knee prosthesis. Based on the materials, three areas of scientific inquiry involving control interfaces for intention detection in active prosthetic legs have been identified. The studies were assessed using the Downs and Black checklist, and their control techniques as well as the performance assessment for these control interfaces are described. After screening, 211 studies were retrieved and examined, however only 39 publications were included and examined in this review. An active prosthetic leg's control strategy framework and goal output were examined in fifteen (15) papers. In two (2) papers, conventional control methods for transfemoral prosthetic legs were examined. Eight (8) further research looked at the potential implementation of intent detection in the transfemoral prosthetic leg, while fourteen (14) papers explored the active prosthetic leg's machine learning algorithm. As a result, our research showed that using a less complex sensory system to control an active transfemoral prosthetic limb is possible when paired with a creative approach and control algorithm that can translate the restricted sensor data into a larger set of relevant data. Therefore, an effective sensory system (practicality and quality of the sensory input) and intention detection algorithm were required for an active transfemoral prosthetic limb. It is considered a complex activity because of the connected biomechanics of human gait, which the brain governs unconsciously. No prosthetic device has been able to replace a human limb in the same way that the original one would operate due to the ongoing challenges in prosthetic technology. Even with something as simple as walking, there are several components to the difficulty that may be broken down into different study areas. No matter how little, this calls for input from many different domains of knowledge. Considerations for future development might be based on this current analysis of the intention-detecting control interface of active knee prosthetic devices and prosthetic technology. This evaluation of the literature includes not only a study of the viability of control interfaces that support intention detection for an active prosthetic limb, but it also suggests a framework for categorizing various works in the subject.

Repetitive electrically-evoked muscle contractions lead to the early onset of muscle fatigue. This study assessed the relationship between muscle mechanomyography (%RMS-MMG) and tissue oxygen saturation (%TSI) in extensor carpi radialis (ECR) during electrically-evoked fatiguing exercise in individuals with tetraplegia.Skin-surface mechanomyography (MMG) and near-infrared spectroscopy (NIRS) sensors were placed on the ECR of seven individuals with tetraplegia. All participants performed repetitive electrically-evoked wrist extension to fatigue while their muscle MMG and NIRS responses were monitored against their power output (PO).One out of seven participants showed no changes in %TSI throughout the repeated wrist FES-evoked contraction. The other six participants' %TSI was positively correlated with %PO before fatigue onset. At 50%POThe significant changes in muscle mechanomyography and tissue oxygenation correlations after 50%PO

Leg exercises through standing, cycling and walking with/without FES may be used to preserve lower limb muscle and bone health in persons with physical disability due to SCI. This study sought to examine the effectiveness of leg exercises on bone mineral density and muscle cross-sectional area based on their clinical efficacy in persons with SCI. Several literature databases were searched for potential eligible studies from the earliest return date to January 2022. The primary outcome targeted was the change in muscle mass/volume and bone mineral density as measured by CT, MRI and similar devices. Relevant studies indicated that persons with SCI that undertook FES- and frame-supported leg exercise exhibited better improvement in muscle and bone health preservation in comparison to those who were confined to frame-assisted leg exercise only. However, this observation is only valid for exercise initiated early (i.e., within 3 months after injury) and for ≥30 min/day for ≥ thrice a week and for up to 24 months or as long as desired and/or tolerable. Consequently, apart from the positive psychological effects on the users, leg exercise may reduce fracture rate and its effectiveness may be improved if augmented with FES.

Call bell systems play an essential role in patient and nurse interaction in hospitals and at homes. However, many hospitalized patients, especially patients with tetraplegia, cannot press a call bell button for assistance due to hand weakness or paralysis from the neck down. This problem has motivated developing a fabric-based multi-array pressure sensor as a call bell garment, named ePillow, that works by detecting the pressure pattern on a pillow surface where the patient is lying down. In this study, off-the-shelf materials were utilized to form: i) a fabric-based multi-array pressure sensor system, ii) an acquisition circuit along with an interface, and iii) a signal processing algorithm to acquire and interpret the sensor data. To ensure the functionality of the proposed ePillow, a color-coded mesh plot was developed to visualize the sensor data. The reliability of the system was tested with two individuals. The pressure profile of the proposed ePillow shows a comparable profile to that of the commercialized pressure sensor. Findings from this case study have demonstrated the ability to map the force on the surface of the pillow and subsequently the location of the force applied with 71% accuracy and 70% sensitivity.

Execution of Sit-to-Stand (SitTS) in incomplete spinal cord injury (SCI) patients involves motor function in both upper and lower extremities. The use of arm support, in particular, is a significant assistive factor while executing SitTS movement in SCI population. In addition, the application of functional electrical stimulation (FES) onto quadriceps and gluteus maximus muscles is one of the prescribed management for incomplete SCI to improve muscle action for simple lower limb movements. However, the relative contribution of upper and lower extremities during SitTS has not been thoroughly investigated. Two motor incomplete SCI paraplegics performed repetitive SitTS to fatigue exercise challenge. Their performance was investigated as a mixed-method case-control study comparing SitTS with and without the assistance of FES. Three sets of SitTS tests were completed with 5-min resting period allocated in between sets, with mechanomyography (MMG) sensors attached over the rectus femoris muscles bilaterally. The exercise was separated into 2 sessions; Day 1 for voluntary SitTS and Day 2 for FES-assisted SitTS. Questionnaires were conducted after every session to gather the participants' input about their repetitive SitTS experience. The analysis confirmed that a SitTS cycle could be divided into three phases; Phase 1 (Preparation to stand), Phase 2 (Seat-off), and Phase 3 (Initiation of hip extension), which contributed to 23% ± 7%, 16% ± 4% and 61% ± 6% of the SitTS cycle, respectively. The contribution of arms and legs during SitTS movement varied in different participants based on their legs' Medical Research Council (MRC) muscle grade. In particular, the applied arm forces start to increase clearly when the leg forces start to decline during standing. This finding is supported by the significantly reduced MMG signal indicating leg muscle fatigue and their reported feeling of tiredness.

The aim of this study was to investigate the performance of mechanomyography (MMG) and electromyography (EMG) in monitoring the sternocleidomastoid (SCM) as accessory respiratory muscles when breathing during singing.MMG and EMG were used to record the activity of the SCM in 32 untrained singers reciting a monotonous text and a standard folk song. Their voices were recorded and their pitch, or fundamental frequency (FF), and intensity were derived using Praat software. Instants of inhale and exhales were identified during singing from their voice recordings and the corresponding SCM MMG and EMG activities were analysed.The SCM MMG, and EMG signals during breathing while singing were significantly different than breathing at rest (p0.001). On the other hand, MMG was relatively better correlated to voice intensity in both reading and singing than EMG. EMG was better, but not significantly, correlated with FF in both reading and singing as compared to MMG.This study established MMG and EMG as the quantitative measurement tool to monitor breathing activities during singing. This is useful for applications related to singing therapy performance measure including potentially pathologically effected population. While the MMG and EMG could not distinguish FF and intensity significantly, it is useful to serve as a proxy of inhalation and exhalation levels throughout a particular singing session. Further studies are required to determine its efficacy in a therapeutic setting.

Augmentative and alternative communication (AAC) device is one type of AAC which can be used to communicate besides oral speech. It has high potential to assist people with speech disabilities including elderly with aphasia (EWA) to communicate with others. This study was conducted using a newly built AAC device, TalkMate™, as a reference for AAC devices. This study aims to explore the views and perception of users regarding the use of AAC device for elderly with aphasia living in Malaysia. The EWA participants recruited for this study varied in age, severity level and experience with AAC. A qualitative design with five focus groups was conducted. The focus group discussion included caretakers, healthcare professionals and AAC device developers to gain information about multiple perspectives on AAC device use. Thematic analysis yielded four key themes: needs of using AAC, decision on using AAC, resources, and potential improvement of AAC for EWAs. This study highlighted the importance of understanding the needs of EWAs, decision, improvement on the quality of life of the EWAs, and the future of using AAC device. The main barriers of using AAC were identified to be due to funding and access to devices.

Micro-processor controlled prosthetic legs (MPCPL) offer better functionality than conventional prosthetic legs as they use actuators to replace missing joint function. This potentially reduces the user’s metabolic energy consumption and normal walking gait can be mimicked as closely as possible. However, MPCPL require a good control system to perform efficiently, and one of the essential components is the system of sensors. The sensory system must satisfy two important criteria; the practicality in donning and doffing the prosthesis, i.e. the process of putting on and taking off the prosthesis by the amputee user, and the quality in the information provided. In this paper, a comprehensive review was conducted on studies related to the state of the art of sensory system adopted in MPCPL. The publications were searched using four electronics databases within the last 13 years. A total of 31 papers were reviewed. The articles were classified into three main categories: prosthetic-device oriented, user’s-biological-input oriented and neuro-mechanical fusion sensory system. Types of sensors used and their application to the prosthetic system were analyzed. This review indicates that the sensors technology reported in the literature still does not fulfil the criteria of an efficient sensory system. Hence, a sensory system that eases the don and doff process of the prosthesis, yet informative in terms of providing enough useful data to effectively control the prosthesis, is needed for a successful MPCPL.

This study investigates whether mechanomyography (MMG) produced from contracting muscles as a measure of their performance could be a proxy of muscle fatigue during a sustained functional electrical stimulation (FES)-supported standing-to-failure task. Bilateral FES-evoked contractions of quadriceps and glutei muscles, of four adults with motor-complete spinal cord injury (SCI), were used to maintain upright stance using two different FES frequencies: high frequency (HF – 35 Hz) and low frequency (LF – 20 Hz). The time at 30° knee angle reduction was taken as the point of critical “fatigue failure”, while the generated MMG characteristics were used to track the pattern of force development during stance. Quadriceps fatigue, which was primarily responsible for the knee buckle, was characterized using MMG-root mean square (RMS) amplitude. A double exponential decay model fitted the MMG fatigue data with good accuracy [R2 = 0.85–0.99; root mean square error (RMSE) = 2.12–8.10] implying changes in the mechanical activity performance of the muscle’s motor units. Although the standing duration was generally longer for the LF strategy (31–246 s), except in one participant, when compared to the HF strategy, such differences were not significant (p > 0.05) but suggested a faster muscle fatigue onset during HF stimulation. As MMG could discriminate between different stimulation frequencies, we speculate that this signal can quantify muscle fatigue characteristics during prolonged FES applications.

Functional electrical stimulation (FES) has been used to produce force-related activities on the paralyzed muscle among spinal cord injury (SCI) individuals. Early muscle fatigue is an issue in all FES applications. If not properly monitored, overstimulation can occur, which can lead to muscle damage. A real-time mechanomyography (MMG)-based FES system was implemented on the quadriceps muscles of three individuals with SCI to generate an isometric force on both legs. Three threshold drop levels of MMG-root mean square (MMG-RMS) feature (thr50, thr60, and thr70; representing 50%, 60%, and 70% drop from initial MMG-RMS values, respectively) were used to terminate the stimulation session. The mean stimulation time increased when the MMG-RMS drop threshold increased (thr50: 22.7 s, thr60: 25.7 s, and thr70: 27.3 s), indicating longer sessions when lower performance drop was allowed. Moreover, at thr70, the torque dropped below 50% from the initial value in 14 trials, more than at thr50 and thr60. This is a clear indication of muscle fatigue detection using the MMG-RMS value. The stimulation time at thr70 was significantly longer (p = 0.013) than that at thr50. The results demonstrated that a real-time MMG-based FES monitoring system has the potential to prevent the onset of critical muscle fatigue in individuals with SCI in prolonged FES sessions.

Hearing loss is a common neurodegenerative disease that can start at any stage of life. Misalignment of the auditory neural impairment may impose challenges in processing incoming auditory stimulus that can be measured using electroencephalography (EEG). The electrophysiological behaviour response emanated from EEG auditory evoked potential (AEP) requires highly trained professionals for analysis and interpretation. Reliable automated methods using techniques of machine learning would assist the auditory assessment process for informed treatment and practice. It is thus highly required to develop models that are more efficient and precise by considering the characteristics of brain signals. This study aims to provide a comprehensive review of several state-of-the-art techniques of machine learning that adopt EEG evoked response for the auditory assessment within the last 13 years. Out of 161 initially screened articles, 11 were retained for synthesis. The outcome of the review presented that the Support Vector Machine (SVM) classifier outperformed with over 80% accuracy metric and was recognized as the best suited model within the field of auditory research. This paper discussed the comprehensive iterative properties of the proposed computed algorithms and the feasible future direction in hearing impaired rehabilitation.

Individuals with paraplegia spend their time on the wheelchair for life. Adapting to prolonged wheelchair seating for almost all activities of daily living is challenging. The loss of abilities to sense any pain or excessive seating pressure cause them to remain seated on the wheelchair without any pressure relief activities. This situation leads to secondary complications including pressure ulcer which further degrades the individual's health. To overcome this, a wheelchair seating pressure relief training system (WSETs) was developed. Optimal placement of the force sensitive resistors (FSR) as seating pressure sensors on the cushion were determined, and their responses were investigated with 5 paraplegics. Two different FSR orientations, A and B, were compared. Each paraplegic sat in resting position and then performed pressure relief activities (PRA) which included whole body push-up, left and right lean and forward lean, before returning to resting position. Orientation B, with more forward positioned FSRs, showed higher sensitivity, implying better capture of high-risk area of pressure ulcer development. The FSR sensor readings were significantly different among pressure relief activities in all subjects (p < 0.05) indicating the validity of FSR measures for the intended application. In conclusion, the WSETs system was proven suitable as a training tool for new paraplegics to habituate themselves in performing PRA.

Gait detection is crucial especially in active prosthetic leg control mechanism. Vision system, floor sensors, and wearable sensors are the popular methods proposed to collect data for gait detection. However, in active prosthetic leg control, a tool that is practical in its implementation and is able to provide rich gait information is important for effective manipulation of the prosthetic leg. This paper aims to ascertain the feasibility of the piezoelectric-based in-socket sensory system that is hypothesized to be practical in implementation and provide sufficient information as a wearable gait detection tool for transfemoral prosthetic users. Fifteen sensors were instrumented to the anterior and posterior internal wall of a quadrilateral socket. One transfemoral amputee subject donned the instrumented socket and performed two walking routines; single stride and continuous walking. The sensors’ responses from both routines were analyzed with respect to the gait phases. The results suggested that the sensors output signal corresponds to the force components behavior of the stump while performing gait. All sensors were seen active during the first double support period (DS1). The anterior sensors were prominent during the initial swing (Sw), while posterior sensors were active during terminal Sw. These findings correspond with the muscle activity during the respective phases. Besides, the sensors also show significant pattern during single support and the second double support (DS2) phase. Thus, it can be deduced that the proposed sensory system is feasible to be used as a gait phase identification tool.

Loss of sensory motor function is one of the main causes of physical and activity limitations among individual with spinal cord injury (SCI). SCI may lead to muscle paralysis, weakness and disused muscle atrophy. Evidences have shown electrical stimulation and strengthening exercise might improve lower limb muscle strength and size among individual with SCI. Functional electrical stimulation (FES) evoked cycling is one of the methods that can elicit leg muscle contractions in order to produce a cycling motion and promote the integrity of the involved muscles. Therefore, this review is to synthesize the scientific literature regarding the effects of multiple dosages of FES-evoked lower limb cycling on muscle properties. A systematic literature search from 1946 to 2016 was performed. From over 1,139 articles retrieved from the database, about 31 potentially relevant articles were retained for possible inclusion. However, only 10 articles out of 31 articles fulfilled the inclusion criteria. Although the available evidence is compelling, there is insufficient quantity and quality evidence to draw conclusions regarding the specific parameter of FES-CE that may optimally increase muscle strength, mass, and circumference. However, it can be safely concluded that an effective training session would spend for 45-60 min, 3 times a week for at least 4 weeks to see changes in muscle size and strength.

Background Functional Electrical Stimulation (FES) technologies can facilitate standing in persons with spinal cord injury (SCI), and prolonged standing elicited via FES may offer both functional and therapeutic benefits to users. However, the current attainable FES-evoked standing duration is typically short and below the threshold for clinical efficacy. To promote the objective selection of suitable control strategies to restore prolonged and higher-quality standing duration, this study summarised current and emerging approaches to FES standing. Method PubMed, IEEE Xplore,Web of Science and Google Scholar databases were searched for relevant studies on FES-evoked standing after SCI between the earliest return date and December 2017. Thereafter, the quality of all included studies was objectively evaluated using the Downs and Black methodological assessment checklist. Results Twenty-five full-length articles, with mean methodological quality score of 56%, met the inclusion criteria and were retained for analysis. Recent advancements to promote prolonged standing relied greatly on the use of voluntary upper extremities for balancing with arm engaged or disengaged. Some widely-reported constraints were issues of unpredictable postural sway, and unusual muscle responses and perturbations, such as spasm or spasticity, which diminished the reliability of the standing control sensors and algorithms. Conclusion Closed-loop control of FES-supported standing with arms-free modality and voluntary upper extremity balancing promoted the “longest” standing duration and “highest” efficacy among the reported methods, albeit with a limited successful transfer of the technology into the routine clinical practice or community deployment. However, open-loop control of FES standing appeared popular, particularly for its therapeutic gains, simplicity of use and other health and psychological benefits associated with weight bearing through the legs. The information from this study could stimulate useful knowledge that may promote clinically significant FES-supported standing duration.

Previous research investigated recumbent cycle power output (PO) from the perspective of knee and hip joint biomechanics. However, ankle-foot biomechanics and, in particular, the effect of ankle-foot orthosis (AFO)-constrained movements on cycle PO has not been widely explored. Therefore, the purpose of this study was to determine whether AFOs of a fixed position (FP) and in dorsi-plantarflexion (DPF)-, dorsiflexion (DF)- and plantarflexion (PF)-constrained movements might influence PO during voluntary recumbent cycling exercises. Twenty-five healthy individuals participated in this study. All underwent 1-min cycling at a fixed cadence for each of the AFOs. The peak and average PO of each condition were analyzed. The peak and average PO were 27.2±12.0 W (range 6–60) and 17.2±9.0 W (range 2–36), respectively, during voluntary cycling. There were no significant differences in the peak PO generated by the AFOs (p=0.083). There were also no significant differences in the average PO generated using different AFOs (p=0.063). There were no significant differences in the changes of the hip and knee joint angles with different AFOs (p=0.974 and p=1.00, respectively). However, there was a significant difference in the changes of the ankle joint angle (p

Background Investigation of muscle fatigue during functional electrical stimulation (FES)-evoked exercise in individuals with spinal cord injury using dynamometry has limited capability to characterize the fatigue state of individual muscles. Mechanomyography has the potential to represent the state of muscle function at the muscle level. This study sought to investigate surface mechanomyographic responses evoked from quadriceps muscles during FES-cycling, and to quantify its changes between pre- and post-fatiguing conditions in individuals with spinal cord injury. Methods Six individuals with chronic motor-complete spinal cord injury performed 30-min of sustained FES-leg cycling exercise on two days to induce muscle fatigue. Each participant performed maximum FES-evoked isometric knee extensions before and after the 30-min cycling to determine pre- and post- extension peak torque concomitant with mechanomyography changes. Findings Similar to extension peak torque, normalized root mean squared (RMS) and mean power frequency (MPF) of the mechanomyography signal significantly differed in muscle activities between pre- and post-FES-cycling for each quadriceps muscle (extension peak torque up to 69%; RMS up to 80%, and MPF up to 19%). Mechanomyographic-RMS showed significant reduction during cycling with acceptable between-days consistency (intra-class correlation coefficients, ICC = 0.51–0.91). The normalized MPF showed a weak association with FES-cycling duration (ICC = 0.08–0.23). During FES-cycling, the mechanomyographic-RMS revealed greater fatigue rate for rectus femoris and greater fatigue resistance for vastus medialis in spinal cord injured individuals. Interpretation Mechanomyographic-RMS may be a useful tool for examining real time muscle function of specific muscles during FES-evoked cycling in individuals with spinal cord injury.

In deep learning, convolutional neural network (CNN) mostly apply common overland images instead of underwater images classifiers. Even though there are few classifiers that have been introduced in marine and aquaculture application, there is still limited sources of the underwater images such as shrimp images. Generally, most conventional management systems in shrimp aquaculture implemented manual techniques that highly depend on human to observe shrimp conditions. One of the major problems of shrimp aquaculture is the challenge of recognizing underwater images, despite the characteristic atmosphere such as the murky and turbid water conditions. Many models of image classification have been introduced in order to solve the issue of early detection in shrimp and ponds problems. However, there are several limitations of the proposed methods such as semi-intelligence or fully wired systems. Therefore, an intelligence computational method and wireless system or internet of things (IoT)-based system is crucial in making sure a precision aquaculture farming. This study conducted a transfer learning model for CNN real time shrimp recognition. This study aims to accurately assess the performance of the developed CNN model by evaluating shrimp images based on intersection over union (IoU) between annotation and proposed models. The result shows the proposed model can successfully detect the shrimps with more than 95% accuracy. As a conclusion, the proposed model is able to detect the real time video recognition of underwater shrimp in ponds and is applicable in wireless farming.

A transfemoral prosthesis is required to assist amputees to perform the activity of daily living (ADL). The passive prosthesis has some drawbacks such as utilization of high metabolic energy. In contrast, the active prosthesis consumes less metabolic energy and offers better performance. However, the recent active prosthesis uses surface electromyography as its sensory system which has weak signals with microvolt-level intensity and requires a lot of computation to extract features. This paper focuses on recognizing different phases of sitting and standing of a transfemoral amputee using in-socket piezoelectric-based sensors. 15 piezoelectric film sensors were embedded in the inner socket wall adjacent to the most active regions of the agonist and antagonist knee extensor and flexor muscles, i. e. region with the highest level of muscle contractions of the quadriceps and hamstring. A male transfemoral amputee wore the instrumented socket and was instructed to perform several sitting and standing phases using an armless chair. Data was collected from the 15 embedded sensors and went through signal conditioning circuits. The overlapping analysis window technique was used to segment the data using different window lengths. Fifteen time-domain and frequency-domain features were extracted and new feature sets were obtained based on the feature performance. Eight of the common pattern recognition multiclass classifiers were evaluated and compared. Regression analysis was used to investigate the impact of the number of features and the window lengths on the classifiers’ accuracies, and Analysis of Variance (ANOVA) was used to test significant differences in the classifiers’ performances. The classification accuracy was calculated using k-fold cross-validation method, and 20% of the data set was held out for testing the optimal classifier. The results showed that the feature set (FS-5) consisting of the root mean square (RMS) and the number of peaks (NP) achieved the highest classification accuracy in five classifiers. Support vector machine (SVM) with cubic kernel proved to be the optimal classifier, and it achieved a classification accuracy of 98.33 % using the test data set. Obtaining high classification accuracy using only two time-domain features would significantly reduce the processing time of controlling a prosthesis and eliminate substantial delay. The proposed in-socket sensors used to detect sit-to-stand and stand-to-sit movements could be further integrated with an active knee joint actuation system to produce powered assistance during energy-demanding activities such as sit-to-stand and stair climbing. In future, the system could also be used to accurately predict the intended movement based on their residual limb’s muscle and mechanical behaviour as detected by the in-socket sensory system.

Background Due to its clinically proven safety and health benefits, functional electrical stimulation (FES) cycling has become a popular exercise modality for individuals with spinal cord injury (SCI). Since its inception in 2013, the Cybathlon championship has been a platform for publicizing the potential of FES cycling in rehabilitation and exercise for individuals with SCI. This study aimed to evaluate the contribution of the Cybathlon championship to the literature on FES cycling for individuals with SCI 3 years pre and post the staging of the Cybathlon championship in 2016. Methods Web of Science, Scopus, ScienceDirect, IEEE Xplore, and Google Scholar databases were searched for relevant studies published between January 2013 and July 2019. The quality of the included studies was objectively evaluated using the Downs and Black checklist. Results A total of 129 articles on FES cycling were retained for analysis. A total of 51 articles related to Cybathlon were reviewed, and 14 articles were ultimately evaluated for the quality. In 2017, the year following the Cybathlon championship, Web of Science cited 23 published studies on the championship, which was almost 5-fold more than were published in 2016 (n = 5). Training was most often reported as a topic of interest in these studies, which mostly (76.7%) highlighted the training parameters of interest to participating teams in their effort to maximize their FES cycling performance during the Cybathlon championship. Conclusion The present study indicates that the Cybathlon championship in 2016 contributed to the number of literature published in 2017 on FES cycling for individuals with SCI. This finding may contribute to the lessons that can be learned from participation in the Cybathlon and potentially provide additional insights into research in the field of race-based FES cycling.