Neurorehabilitation Platform Based on EEG, sEMG and Virtual Reality Using Robotic Monocycle

Cardoso, Vivianne; Pomer-Escher, Alexandre; Longo, Berthil; Loterio, Flávia Aparecida; Nascimento, Sara S. G.; Laiseca, María Alejandra Romero; Delisle-Rodríguez, Denis; Frizera, Anselmo; Bastos, Teodiano

doi:10.1007/978-981-13-2119-1_48

Cited by 8 publications

(7 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, another novel BCI application was identified using entertainment and/or sport devices. The publication in [ 45 ] proposed to use a robotic monocycle, a neurorehabilitation platform based on EEG, surface electromyography (sEMG) and immersive virtual reality (IVR) to move the user’s legs. The system consisted of a customized electronic board to control the monocycle according to the user’s MI, sEMG signals that were collected from the leg muscles in order to identify onset and displacement, a serious game, and the monocycle, which was equipped with inertial sensors placed on the pedals that were used to measure the cadence developed by the user while pedaling.…”

Section: Resultsmentioning

confidence: 99%

“…Finally, obtaining the highest percentage, there were 11 studies involving non-immersive virtual reality. There were the following: a game proposed in [ 30 ], which showed greater effectiveness compared to traditional rehabilitation, a wheelchair [ 31 ], the system to control a mobile robot based on EEG analysis, and two mental tasks (relaxed state and motor imagination of the right hand) [ 36 ], systems with FES [ 37 , 42 ], the system that decoded lower limb joint angles during walking [ 40 ], the rehabilitation hand [ 46 ] and the robotic monocycle of [ 45 ].…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Brain-Computer Interfaces Systems for Upper and Lower Limb Rehabilitation: A Systematic Review

Camargo-Vargas

Callejas-Cuervo

Mazzoleni

2021

Sensors

View full text Add to dashboard Cite

In recent years, various studies have demonstrated the potential of electroencephalographic (EEG) signals for the development of brain-computer interfaces (BCIs) in the rehabilitation of human limbs. This article is a systematic review of the state of the art and opportunities in the development of BCIs for the rehabilitation of upper and lower limbs of the human body. The systematic review was conducted in databases considering using EEG signals, interface proposals to rehabilitate upper/lower limbs using motor intention or movement assistance and utilizing virtual environments in feedback. Studies that did not specify which processing system was used were excluded. Analyses of the design processing or reviews were excluded as well. It was identified that 11 corresponded to applications to rehabilitate upper limbs, six to lower limbs, and one to both. Likewise, six combined visual/auditory feedback, two haptic/visual, and two visual/auditory/haptic. In addition, four had fully immersive virtual reality (VR), three semi-immersive VR, and 11 non-immersive VR. In summary, the studies have demonstrated that using EEG signals, and user feedback offer benefits including cost, effectiveness, better training, user motivation and there is a need to continue developing interfaces that are accessible to users, and that integrate feedback techniques.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Brain-Computer Interfaces Systems for Upper and Lower Limb Rehabilitation: A Systematic Review

Camargo-Vargas

Callejas-Cuervo

Mazzoleni

2021

Sensors

View full text Add to dashboard Cite

show abstract

“…We highlight from our approach that it does not depend on specific cycling ergometers or hardware (Chen et al 2017) since it estimates the cadence based on user's hip kinematics instead of crank angle of the ergometer likewise (Cardoso et al 2019;Ferreira et al 2019;Grani and Bruun-Pedersen 2017). The easiness and accessibility of the setup sets the universality of the system, yet being useful as virtual rehabilitation solution in day-care centres, rehabilitation clinics or even for home-based therapies.…”

Section: Discussionmentioning

confidence: 99%

“…Also, in the near future, we plan to improve the design of the virtual scenarios to allow different uses of the tracking sensor, for example, to capture circular movements for the upper limb. Another positive aspect is that our approach is perfectly portable and simple to assemble, unlike the systems proposed by Cardoso et al (2019), Ferreira et al (2019 and Grani and Bruun-Pedersen (2017), which are based on the mechanical adaptation of commercial ergometers crank/pedals or custom hardware developments.…”

Section: Discussionmentioning

confidence: 99%

“…On the other hand, the approaches found in the literature in this field rely on high-cost robotic systems and complex and highly specialised equipment. Cardoso et al (2019) developed a neurorehabilitation platform using a robotic monocycle instrumented with inertial sensors to measure cadence. They also customized an electronic board to control the virtual monocycle with user's motor imagery of electroencephalography (EEG) and surface electromyography (sEMG).…”

Section: Immersive Environments For Indoor Cycling Trainingmentioning

confidence: 99%

See 1 more Smart Citation

Virtual reality application for real-time pedalling cadence estimation based on hip ROM tracking with inertial sensors: a pilot study

2022

View full text Add to dashboard Cite

Virtual reality (VR) applications on rehabilitation a home-base exercise experiences have boomed in the last decade. This is mainly because their entertainment capacity creates a sense of immersion in the users, which enhances adherence to their use. In addition, offering body-related visual feedback is a proven approach to the physical training towards a goal. Recent literature showed the exercise of pedalling has the potential to provide a high number of flexion and extension repetitions of the lower limb in reasonable therapeutic time periods to improve muscle activity, strength and balance in elders, but also motor improvements in patients with neurological injuries. The objective of this work is to present a low-cost wireless application in virtual reality (VR) for pedalling exercises. The platform developed consists of a VR headset and an inertial measurement unit (IMU). The VR headset processes the kinematic information of the IMU to estimate the cadence of the pedalling, while the IMU sensor tracks the angle of hip flexion/extension movement of the user. In order to confirm the suitability of this cadence estimation system, our approach is confronted with a cycling platform developed and validated in a previous study. In the present study, we carried out two repeated sessions with 13 subjects at 3 set speeds: slow (30 rpm), medium (60 rpm) and fast (90 rpm). The Spearman’s correlation (PC) between both systems for the 3 speeds and sessions shows high correlation values for low and medium speeds and moderate correlation for high speed. The SEM results for each system show low measurement error (about 1 cycle) for both systems at every target speed, except for the virtual cycling platform at the highest speed (SEM of VCP at 90 rpm = 3.24 cycles). The repeatability analysis based on ICC (3, 1) absolute agreement shows consistency in all measurements for both systems at high speed and also reflects the irregularity in measurements at low and medium speeds, where participants were less stable during testing due to entertainment from the VR system. All in all, it is concluded the validity of the cadence estimation system for pedalling exercises with low intensity. This development allows us to control the virtual environment by adapting the visual stimulus to cycling cadence. The proposed system can generate sensitive inputs to influence the user’s pedalling cadence.

show abstract

Virtual Reality Cycling Platform for Lower Limb Rehabilitation

Rojo,

Olmo-Fajardo,

Raya

et al. 2024

Biosystems &Amp; Biorobotics

View full text Add to dashboard Cite

Neurorehabilitation Platform Based on EEG, sEMG and Virtual Reality Using Robotic Monocycle

Cited by 8 publications

References 13 publications

Brain-Computer Interfaces Systems for Upper and Lower Limb Rehabilitation: A Systematic Review

Brain-Computer Interfaces Systems for Upper and Lower Limb Rehabilitation: A Systematic Review

Virtual reality application for real-time pedalling cadence estimation based on hip ROM tracking with inertial sensors: a pilot study

Virtual Reality Cycling Platform for Lower Limb Rehabilitation

Contact Info

Product

Resources

About