An Intelligent Control Scheme to Facilitate Abrupt Stopping on Self-Adjustable Treadmills

Asl, Hamed Jabbari; Pyo, Sanghun; Yoon, Jungwon

doi:10.1109/icra.2018.8462897

Cited by 9 publications

(7 citation statements)

References 12 publications

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“…In this mode, the distance between the robot and the user is maintained with no interaction forces between them; i.e., the robot should reach the desired distance from the user, x d , and then match the user's velocity, v w , as shown in Figure 2(a). The implemented control scheme is similar to that of a self-paced treadmill in which the velocity of the belt is matched to the user's velocity [39]. The user's initial gait speed was estimated with a robust integral of the sign of the error (RISE) controller and a low-gain observer.…”

Section: Design Of the Distance Modementioning

confidence: 99%

Development of a Robotic Companion to Provide Haptic Force Interaction for Overground Gait Rehabilitation

et al. 2020

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The aim of gait rehabilitation is to achieve independent ambulation. Somatosensory augmentation with external haptic sources can improve the subject's ability to walk or stand. This paper presents the development and evaluation of a robotic system prototype that delivers haptic forces to aid overground gait rehabilitation. This portable system is based on a compact, mobile robot that is equipped with force and LIDAR sensors. The robot is flexibly linked to the user, which allows the force interaction between the user and machine to be halted when desired. During operation, the system can dynamically transition between modes in which force is applied or distance is maintained to emulate the experience of a human walking a dog on a leash. The haptic feedback from our system was evaluated in a pilot study that involved six young, healthy subjects and one individual recovering from a hemiparetic stroke. The study comprised independent and device-assisted walking trials. When using the device, the subjects walked continuously as it transitioned between distance and force modes. Gait speed and step length increased when force was applied and decreased as the force was removed. The improvements exhibited by an individual suffering from stroke were similar to those exhibited by healthy subjects. The application of haptic forces has a high potential for improving the efficiency of overground gait training with simple interactions. INDEX TERMS Haptic interfaces, rehabilitation robotics, mobile robots.

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Section: Design Of the Distance Modementioning

confidence: 99%

Development of a Robotic Companion to Provide Haptic Force Interaction for Overground Gait Rehabilitation

et al. 2020

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“…Although previous researches [3] have found that the main factor affecting the UX is users' position errors in the abrupt stop stage. This study maintains that such errors are just one of the main reasons affecting the UX, and other reasons also include the system's working delay and the height of the center of gravity.…”

Section: Main Factors Affecting Users' Experiencementioning

confidence: 87%

“…According to the above results, the UX needs to be further improved. Although HCMK1 has many advantages in its design, like other drivenbased ODTs, the UX would ultimately depend on performance of the controller [3,10]. This is a human-computer interaction problem.…”

Section: Main Factors Affecting Users' Experiencementioning

confidence: 99%

Strolling in Room-Scale VR: Hex-Core-MK1 Omnidirectional Treadmill

Wang¹,

Liu²,

Chen³

et al. 2022

Preprint

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“…The user's IWS is considered as a disturbance input for the UDT because their walking behavior causes their position to change. Thus, the IWS can be estimated from the position information of the user's center of mass (COM) [9][10][11][12]. Souman et.…”

Section: Introductionmentioning

confidence: 99%

A Sensitive and Accurate Walking Speed Prediction Method Using Ankle Torque Estimation for a User-Driven Treadmill Interface

2022

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To achieve safe and immersive interface with a user-driven treadmill (UDT), robustness of the user position must be ensured by sensitively estimating and accurately converging to the intentional walking speed (IWS). The existing IWS estimation using a linear observer with the cart model (1 st order dynamics) can exponentially converge to the true IWS. However, when the estimation sensitivity is increased by increasing the gain, this method causes severe postural instability due to the generation of excessive anomalous forces. Thus, the existing method has an implicit limitation with regards to increasing the position robustness because of the postural instability issues. In this paper, to simultaneously achieve sensitive and accurate IWS estimation while reducing postural instability on a UDT, in addition to the cart model, we have also utilized the inverted pendulum-based gait model (IPGM) as a 2 nd order dynamic to estimate the intentional walking acceleration (IWA) generated by the ankle torque. Thus, the proposed IWS prediction method uses the cart model for accurate convergence to IWS and the IPGM to follow sensitively the change in the IWS. In the proposed method, the internal states of the existing observers applied to the 1 st and 2 nd order dynamics are shared recursively to estimate the ankle torque acting as a disturbance for the IPGM and to sensitively predict the change in the IWS. Experiments show that the proposed method can significantly facilitate the users in following a profile of desired walking speeds more accurately than the existing IWS estimation method under the same position robustness setup.

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An Intelligent Control Scheme to Facilitate Abrupt Stopping on Self-Adjustable Treadmills

Cited by 9 publications

References 12 publications

Development of a Robotic Companion to Provide Haptic Force Interaction for Overground Gait Rehabilitation

Development of a Robotic Companion to Provide Haptic Force Interaction for Overground Gait Rehabilitation

Strolling in Room-Scale VR: Hex-Core-MK1 Omnidirectional Treadmill

A Sensitive and Accurate Walking Speed Prediction Method Using Ankle Torque Estimation for a User-Driven Treadmill Interface

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