Adaptation of a smart walker for stroke individuals: a study on sEMG and accelerometer signals

Loterio, Flávia Aparecida; Valadão, Carlos; Cardoso, Vivianne; Pomer-Escher, Alexandre; Bastos, Teodiano; Frizera, Anselmo

doi:10.1590/2446-4740.01717

Cited by 7 publications

(1 citation statement)

References 28 publications

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“…Walker assisted gait with healthy subjects has been reported values between 0.17 m/s and 0.29 m/s depending on the body weight bearing patterns of the leg [ 48 ]. In [ 49 ], a gait assisted by a smart walker without orthosis in post-stroke subjects showed gait velocity values between 0.23 m/s and 0.44 m/s. Then, for the three patterns used here, the walking velocity is within that range of the first case, which means that the effect of ALLOR with knee impedance modulation does not produce a significant speed reduction in walker-assisted gait.…”

Section: Resultsmentioning

confidence: 99%

Knee Impedance Modulation to Control an Active Orthosis Using Insole Sensors

Villa-Parra

Delisle-Rodríguez

Lima

et al. 2017

Sensors

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Robotic devices for rehabilitation and gait assistance have greatly advanced with the objective of improving both the mobility and quality of life of people with motion impairments. To encourage active participation of the user, the use of admittance control strategy is one of the most appropriate approaches, which requires methods for online adjustment of impedance components. Such approach is cited by the literature as a challenge to guaranteeing a suitable dynamic performance. This work proposes a method for online knee impedance modulation, which generates variable gains through the gait cycle according to the users’ anthropometric data and gait sub-phases recognized with footswitch signals. This approach was evaluated in an active knee orthosis with three variable gain patterns to obtain a suitable condition to implement a stance controller: two different gain patterns to support the knee in stance phase, and a third pattern for gait without knee support. The knee angle and torque were measured during the experimental protocol to compare both temporospatial parameters and kinematics data with other studies of gait with knee exoskeletons. The users rated scores related to their satisfaction with both the device and controller through QUEST questionnaires. Experimental results showed that the admittance controller proposed here offered knee support in 50% of the gait cycle, and the walking speed was not significantly different between the three gain patterns (p = 0.067). A positive effect of the controller on users regarding safety during gait was found with a score of 4 in a scale of 5. Therefore, the approach demonstrates good performance to adjust impedance components providing knee support in stance phase.

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Section: Resultsmentioning

confidence: 99%

Knee Impedance Modulation to Control an Active Orthosis Using Insole Sensors

Villa-Parra

Delisle-Rodríguez

Lima

et al. 2017

Sensors

Self Cite

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Multimodal Interaction Strategies for Walker-Assisted Gait: A Case Study for Rehabilitation in Post-Stroke Patients

Jimenez,

Mello,

Loterio

et al. 2024

J Intell Robot Syst

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Stroke has been considered the main cause of neuromuscular damages worldwide and one of the most common causes of walking disabilities, with approximately 60% of the individuals suffering from persistent problems in walking. These patients generally use technical aids for walking to achieve independent gait, however, when cognitive impairments are also present, conventional assistive devices such as walkers could be difficult to handle. By leveraging multimodal interfaces, smart walkers can offer natural and intuitive human-robot interaction. In this work, we present two multimodal interaction strategies for smart walkers focusing on guiding post-stroke patients through their environment. These strategies leverage different communication channels and provide distinct levels of guidance: one strategy uses haptic feedback and a visual interface to indicate the desired path to the user, while the other strategy uses haptic feedback and a virtual torque to maintain the user on path. We also present two case studies with post-stroke patients to preliminarily validate these interaction strategies with their target population and to collect valuable insight as to how multimodal strategies for smart walkers can be enhanced to deal with the characteristic asymmetries of post-stroke patients. Our results show that both strategies can guide the volunteers, however, the first one demands more effort from the volunteer and is more suited for patients with increased levels of independence. The second interaction strategy allows for higher linear velocity (Volunteer 1, $$\varvec{0.18}$$ 0.18 $$\varvec{\pm 0.026}$$ ± 0.026 $$\varvec{m/s}$$ m / s ; Volunteer 2, $$\varvec{0.22}$$ 0.22 $$\varvec{\pm 0.0283}$$ ± 0.0283 $$\varvec{m/s}$$ m / s ) than the first one (Volunteer 1, $$\varvec{0.10}$$ 0.10 $$\varvec{\pm 0.031}$$ ± 0.031 $$\varvec{m/s}$$ m / s ; Volunteer 2, $$\varvec{0.20}$$ 0.20 $$\varvec{\pm 0.012}$$ ± 0.012 $$\varvec{m/s}$$ m / s ), suggesting improved guidance.

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