Development and Clinical Evaluation of a Posterior Active Walker for Disabled Children

Ragaja, S. R.; Dinesh, N. S.; Madhuri, Vrisha; Parameswaran, Apurve

doi:10.1007/s10846-019-01009-x

Cited by 10 publications

(14 citation statements)

References 25 publications

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“…A rollator using autonomous or traded-control modes where the robot may be fully in control at a given time can be loosely defined as an active device, meaning that the device may take action even if users are not moving [46]. As independent motion may affect user's balance, recent rollators tend to be passive, e.g.…”

Section: B Operation Modesmentioning

confidence: 99%

“…not specifically adapted to each user. In the reviewed works, assistance: i) supports users to steer to correct orientation [1], [2], [3], [22], [35], [50]; and ii) keeps secure distances between rollator and user [46] and/or between rollator and obstacles, either at the current location [26], or in the near future [50].…”

Section: B Operation Modes In Rollatorsmentioning

confidence: 99%

“…Hemiplegic patient [41] [20], [21], [27], [44], [45], [49], [58] Autonomous-robot Generic Autonomous-robot Personalized Traded-control Generic Traded-control Personalized Shared-control Generic Steering control [1], [2], [3], [22], [29], [31], [35], [38], [50]. Keep distances between the human and the rollator [26], [46], [50]. Fall detection [52].…”

Section: Autonomoushumanmentioning

confidence: 99%

“…Disabled people [31], [35], [46]. People with diagnosis of ischaemic or hemorrhagic stroke [26] [3], [28], [29], [32], [38], [50], [52] Shared-control Personalized Creates a model to forecast human motion to keep the desired situation (separation distance and bearing in the platform) [12].…”

Section: Autonomoushumanmentioning

confidence: 99%

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Smart Rollators Aid Devices: Current Trends and Challenges

Verdezoto

Ballesteros

Urdiales

2022

IEEE Trans. Human-Mach. Syst.

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Mobility loss has a major impact on autonomy. Smart rollators have been proposed to enhance human abilities when conventional devices are not enough. Many human-robot interaction systems have been proposed in the last decade in this area. Comparative analysis shows that mechanical issues aside, they mainly differ in i) equipped sensors and actuators; ii) input interface; iii) operation modes, and iv) adaptation capabilities. This paper presents a review and a tentative taxonomy of approaches during the last 6 years. In total, 92 papers have been reviewed. We have discarded works not focused on humanrobot interaction or focused only on mechanical adaptation. A critical analysis is provided after the review and classification, highlighting systems tested with their target population.

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Section: B Operation Modesmentioning

confidence: 99%

Section: B Operation Modes In Rollatorsmentioning

confidence: 99%

Section: Autonomoushumanmentioning

confidence: 99%

Section: Autonomoushumanmentioning

confidence: 99%

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Smart Rollators Aid Devices: Current Trends and Challenges

Verdezoto

Ballesteros

Urdiales

2022

IEEE Trans. Human-Mach. Syst.

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“…Smart walkers detect the surrounding environment and perform human-computer interaction by installing various sensors on them, such as the research of Ragaj et al [6] mentioned that a good control algorithm can help users use the walker better. Unlike electric wheelchairs, smart walkers do not completely hand over the control of the lower limbs to rehabilitation equipment, but the users themselves control the rehabilitation equipment to complete their walking [7].…”

mentioning

confidence: 99%

Fall Detection System on Smart Walker Based on Multisensor Data Fusion and SPRT Method

et al. 2022

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Traditional walkers are commonly used for the elderly in social life, which solves the basic problem of walking, but it is difficult to ensure safety when a fall occurs, and the human-computer interaction is poor. The image recognition method or the IMU sensor method fixed on the user, such as a wearable watch, is used by most of the current fall detection methods. Wearable sensors require the user's wearing operation, which is a little troublesome, and the detection accuracy is related to the way of wearing. The image recognition method requires a high-priced camera and a fixed installation position, which is unable to adapt to outdoor activities. We investigated a low-cost method of mounting the sensor on the body of the walker. We propose in this paper an improved fall detection method, namely Precondition and Limit Threshold SPRT (PLT-SPRT), and a novel fall detection system on the smart walker based on PLT-SPRT. The signals of the upper and lower limb sensors are fused based on the Kalman filter algorithm, and the admittance control parameters are obtained through the system identification method. In this study, the improved sequential probability ratio test algorithm is used to set the null hypothesis and the alternative hypothesis, construct the likelihood ratio and optimize the decision function, which is used to judge whether falls occur. The system is simulated by Matlab software, the user intention after fusion is more accurate, and the optimized decision function is judged accurately. Verified by the embedded system based on STM32 of the smart walker equipment in the real world, it can accurately identify the fallen state, with low detection delay, and the fallen state is detected about 160ms earlier than the traditional threshold-based detection algorithm, at the same time, the accuracy is higher than 94.9%, which meets the high real-time requirements of fall detection and is the ideal solution for smart walkers.

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