Wireless IMU: A Wearable Smart Sensor for Disability Rehabilitation Training

Kadir, Kushsairy; Yusof, Zulkhairi Mohd; Rasin, Mohaad Zaimhirain Mohamed; Billah, Md. Masum; Salikin, Qisti

doi:10.1109/icssa.2018.8535952

Cited by 4 publications

(5 citation statements)

References 20 publications

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“…The detection of motion based on data collected from IMUs has been widely used for rehabilitation purposes. In [50]- [55], a wireless IMU was used for stroke rehabilitation in combination with or without motion-sensitive games based on VR (IMU-based exergames). IMU information has also been used for biomechanical analysis [56]- [60], such as gait analysis, which can be used to evaluate motor recovery.…”

Section: Discussionmentioning

confidence: 99%

A Versatile Embedded Platform for Implementation of Biocooperative Control in Upper-Limb Neuromotor Rehabilitation Scenarios

et al. 2023

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Biocooperative control uses both biomechanical and physiological information of the user to achieve a reliable human-robot interaction. In the context of neuromotor rehabilitation, such control can enhance rehabilitation experience and outcomes. However, the high cost and large volume of the commercial systems for physiological signal acquisition are major limitations for the development of such control. We present a highly versatile, low-cost and wearable embedded system that integrates the most commonly used sensors in this field: inertial measurement unit (IMU), electrocardiography (ECG), electromyography (EMG), galvanic skin response (GSR) and skin temperature (SKT) sensors. Additionally, the compact system combines wireless communication for data transmission and a high-efficiency microcontroller for real-time signal processing and control. We tested the system in two common neuromotor rehabilitation scenarios. The first is an upper-limb rehabilitation VR-based exergame, in which the patient must collect as many coins as possible. Movement recognition of the hand and arm is performed based on EMG and IMU information, respectively. The second is adaptive assistive control that adjusts the level of assistance of a wrist rehabilitation robot according to the physiological state and motor performance of the patient using GSR, ECG and SKT data. The quality of the recorded signals and the processing capacity of the system meet the needs of the two upper-limb rehabilitation applications. The wearable system is highly versatile, open, configurable and low cost, and it could promote the development of real-time biocooperative control for a wide range of neuromotor rehabilitation applications.INDEX TERMS Biocooperative control, embedded system, neuromotor rehabilitation, real-time signal processing, wearable sensors.

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Section: Discussionmentioning

confidence: 99%

A Versatile Embedded Platform for Implementation of Biocooperative Control in Upper-Limb Neuromotor Rehabilitation Scenarios

et al. 2023

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“…This type of sensor consists of several internal sensors. A 6 Degrees of Freedom (DoF) IMU is commonly used in recent works [7,8]. It has a constant drift in the resulting measurement data that cannot be corrected for.…”

Section: Sensorsmentioning

confidence: 99%

“…By implementing our own sensor fusion and calibration, we can implement the most suited fusion algorithms and have full control over the calibration. Some systems use sensor fusion algorithms like a Kalman filter [7], which provide very accurate results but can be computationally intensive. A complementary filter, which is very easy to process but typically provides less accurate results than a Kalman filter, is sometimes used.…”

Section: Sensorsmentioning

confidence: 99%

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Low-Complexity Design and Validation of Wireless Motion Sensor Node to Support Physiotherapy

Cappelle

Monteyne

Mulders

et al. 2020

Sensors

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We present a motion sensor node to support physiotherapy, based on an Inertial Measurement Unit (IMU). The node has wireless interfaces for both data exchange and charging, and is built based on commodity components. It hence provides an affordable solution with a low threshold to technology adoption. We share the hardware design and explain the calibration and validation procedures. The sensor node has an autonomy of 28 h in operation and a standby time of 8 months. On-device sensor fusion yields static results of on average 3.28° with a drift of 2° per half hour. The final prototype weighs 38 g and measures ø6 cm × 1.5 cm. The resulting motion sensor node presents an easy to use device for both live monitoring of movements as well as interpreting the data afterward. It opens opportunities to support and follow up treatment in medical cabinets as well as remotely.

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“…Since stiff elbow takes a long time to improve, from 6 months to 12 months [ 9 ], the patient should proceed with exercise after hospital discharge, requiring to follow a long-term rehabilitation program during home recovery. Due to the various challenges facing these mechanical devices, alternative ideas for stiff elbow training programs that involve smart wearable device technology for recording patients' movements have been developed in recent years [ 12 – 15 ]. However, these wearable devices require supervision; they are expensive, offer no motivation, and cannot be used outside the clinical environment.…”

Section: Introductionmentioning

confidence: 99%

Design of a Smart Elbow Brace as a Home-Based Rehabilitation Device

Said

Yong

Heyat

et al. 2022

Computational Intelligence and Neuroscience

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Poststroke and traumatic elbow injuries are the most common cause of elbow stiffness, which results in loss of functional range of motion (ROM). Various studies support early mobilization of the elbow joint after injury or after surgery to reduce risks of elbow stiffness development. After hospitalization, patients are required to follow a long-term rehabilitation program during home recovery. Still, most patients do not adhere to their clinical therapy schedule due to either rehabilitation cost, social obligations, negligence, or lack of inspiration. Moreover, the numbers of therapists and assessment equipment are insufficient. This study introduces a smart elbow brace (SEB) as a home-based rehabilitation device that reduces regular in-patient rehabilitation costs and therapist workload and motivates patients to comply with the rehabilitation program that enhances the achievement of rehabilitation goals. Our device has two active degrees of freedom (2-DoF) that allow extension, flexion, pronation, and supination elbow motions. An extra sliding joint between forearm and wrist is added, which helps dump forces concentration at the elbow joint during extension-flexion movement. Mechanical design requirements, motion-tracking systems, and serious game development are described. The feasibility of a proposed SEB device is tested with five healthy subjects playing developed serious games with the device. The results show that subjects can attain maximum and minimum angles of flexion-extension and pronation-supination motion designed for elbow stiffness rehabilitation. The SEB device will be beneficial and be used at home as a complementary tool to support elbow stiffness rehabilitation during long-term home recovery.

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Wireless IMU: A Wearable Smart Sensor for Disability Rehabilitation Training

Cited by 4 publications

References 20 publications

A Versatile Embedded Platform for Implementation of Biocooperative Control in Upper-Limb Neuromotor Rehabilitation Scenarios

A Versatile Embedded Platform for Implementation of Biocooperative Control in Upper-Limb Neuromotor Rehabilitation Scenarios

Low-Complexity Design and Validation of Wireless Motion Sensor Node to Support Physiotherapy

Design of a Smart Elbow Brace as a Home-Based Rehabilitation Device

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