A Control Software Framework for Wearable Mechatronic Devices

Desplenter, Tyler; Trejos, Ana Luisa

doi:10.1007/s10846-019-01144-5

Cited by 3 publications

(6 citation statements)

References 40 publications

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“…Problem formulation To begin with, a typical stroke rehabilitation is decomposed from an algorithmic perspective in this section. In rehabilitation scenarios, session starts with the clinicians assessing the physical impairment of the subject and using the relevant information obtained to define how long each session should be (i.e., number of repetitions per time unit/session) to avoid further injuries like ligament tears, capsule injuries and muscle fatigue [36,37,38,39,40]. For favorable outcomes, it is reported that a given session should last about 36 minutes to 1 hour per day [41].…”

Section: 21mentioning

confidence: 99%

A linear model-based simulation tool for estimating number of trials needed for upper limb stroke recovery in a given rehabilitation session

Faremi,

Ayodele,

Jubril

et al. 2023

Nig. J. Tech.

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Traditional methods for assessing upper-limb functional outcomes in stroke patients often fail to estimate the number of trials required to achieve performance stability of a chosen kinematic metric. Limited non-model-based studies have attempted to tackle this issue. To bridge this gap, this study utilized an iterative learning algorithm (ILA) in MATLAB, employing linear models to represent the muscle dynamics and forearm extension of impaired patients. The reference task space trajectory was set as a straight-line point-point trajectory within a range of 0 - 0.2828m. By using the root mean square error (RMSE) as a metric for evaluating kinematic accuracy, a maximum kinematic deviation error of 0.01m was imposed with respect to the trajectory by the (ILA). Results indicate that over 16 trials, performance stability was obtained with improvement in deviation error from 0.0168m in the first trial to 0.0060 at sixteen trials. The result obtained is in line with similar non-model studies and our findings inform the potential of ILAs with linear models for estimation of trial numbers required to attain performance stability of a selected kinematic metric (i.e., kinematic accuracy).

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Section: 21mentioning

confidence: 99%

A linear model-based simulation tool for estimating number of trials needed for upper limb stroke recovery in a given rehabilitation session

Faremi,

Ayodele,

Jubril

et al. 2023

Nig. J. Tech.

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“…At this level, IoT technology can be utilized to provide proper feedback from the treatment and identification of muscloskeletal parameters for the therapist, as well as therapist supervision. To this end, a mission planning module must be developed proposing a wide variety of options applicable to the mechatronic design; including multiple modalities and training protocols can increase the chance of adoption by medical professionals ( Desplenter and Trejos, 2020 ). According to the specified task, the trajectory planning level plans the kinematic and kinetic parameters of the motion to meet the objectives of the planned mission.…”

Section: Design Paradigmmentioning

confidence: 99%

“…Regarding the safety concerns of home therapy due to the absence of the therapist, highly adaptive control systems need to be developed to consider the differences of the human bodies, the motion tasks during the recovery process for each patient, and the nature of the injury between patients ( Desplenter and Trejos, 2020 ). The control solution has to show an adequate amount of active compliance to avoid hurting the patient in the case of trajectory errors due to abnormal or excessive muscle contraction, spasticity, or other pathological synergies ( Proietti et al, 2016 ).…”

Section: Design Paradigmmentioning

confidence: 99%

“…As control system development tools, there are software frameworks designed to provide developers with a platform for the design and implementation of the control system, (e.g., Tekin et al, 2009 ; Coevoet et al, 2017 ; Desplenter and Trejos, 2020 ). The use of such frameworks supports the idea of standardization across different studies and devices.…”

Section: Design Paradigmmentioning

confidence: 99%

“…WearMECS is a recently developed control software design and implementation tool available as an open-source software library. The framework provides a foundation for regulating the motion behavior of therapeutic mechatronic devices by considering three main control functionality groups, i.e., task-level control, estimation-level control, and actuation-level control ( Desplenter and Trejos, 2020 ).…”

Section: Design Paradigmmentioning

confidence: 99%

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Robotic Home-Based Rehabilitation Systems Design: From a Literature Review to a Conceptual Framework for Community-Based Remote Therapy During COVID-19 Pandemic

2021

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During the COVID-19 pandemic, the higher susceptibility of post-stroke patients to infection calls for extra safety precautions. Despite the imposed restrictions, early neurorehabilitation cannot be postponed due to its paramount importance for improving motor and functional recovery chances. Utilizing accessible state-of-the-art technologies, home-based rehabilitation devices are proposed as a sustainable solution in the current crisis. In this paper, a comprehensive review on developed home-based rehabilitation technologies of the last 10 years (2011–2020), categorizing them into upper and lower limb devices and considering both commercialized and state-of-the-art realms. Mechatronic, control, and software aspects of the system are discussed to provide a classified roadmap for home-based systems development. Subsequently, a conceptual framework on the development of smart and intelligent community-based home rehabilitation systems based on novel mechatronic technologies is proposed. In this framework, each rehabilitation device acts as an agent in the network, using the internet of things (IoT) technologies, which facilitates learning from the recorded data of the other agents, as well as the tele-supervision of the treatment by an expert. The presented design paradigm based on the above-mentioned leading technologies could lead to the development of promising home rehabilitation systems, which encourage stroke survivors to engage in under-supervised or unsupervised therapeutic activities.

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