Identification of Object Dynamics Using Hand Worn Motion and Force Sensors

Kortier, H.G.; Schepers, H. Martin; Veltink, Petrus H.

doi:10.3390/s16122005

Cited by 13 publications

(17 citation statements)

References 27 publications

(36 reference statements)

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“…In the future, the hand sensor system will be combined with fingertip force sensors that detect contact with an object and thus yield additional information when the patient grasps and holds an object [53]. Future work should also aim at a reduction of the sensor system’s weight and dimensions, to further reduce the impact of the system on movements with the motor-impaired hand.…”

Section: Discussionmentioning

confidence: 99%

A Tangible Solution for Hand Motion Tracking in Clinical Applications

Salchow-Hömmen

Callies

Laidig

et al. 2019

Sensors

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Objective real-time assessment of hand motion is crucial in many clinical applications including technically-assisted physical rehabilitation of the upper extremity. We propose an inertial-sensor-based hand motion tracking system and a set of dual-quaternion-based methods for estimation of finger segment orientations and fingertip positions. The proposed system addresses the specific requirements of clinical applications in two ways: (1) In contrast to glove-based approaches, the proposed solution maintains the sense of touch. (2) In contrast to previous work, the proposed methods avoid the use of complex calibration procedures, which means that they are suitable for patients with severe motor impairment of the hand. To overcome the limited significance of validation in lab environments with homogeneous magnetic fields, we validate the proposed system using functional hand motions in the presence of severe magnetic disturbances as they appear in realistic clinical settings. We show that standard sensor fusion methods that rely on magnetometer readings may perform well in perfect laboratory environments but can lead to more than 15 cm root-mean-square error for the fingertip distances in realistic environments, while our advanced method yields root-mean-square errors below 2 cm for all performed motions.

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Section: Discussionmentioning

confidence: 99%

A Tangible Solution for Hand Motion Tracking in Clinical Applications

Salchow-Hömmen

Callies

Laidig

et al. 2019

Sensors

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“…This results in the better cooperation of the limb with the device. Exoskeleton devices are mainly fixed to a wheelchair ( Figure 2 a) [ 11 ] or the floor ( Figure 2 b) [ 1 , 2 , 5 , 12 ]. The main disadvantage of exoskeleton solutions is the significantly complicated mechanism, which results in their very high production cost.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Motion Intentions as a Novel Method of Upper Limb Rehabilitation Support

Lewandowski

Wudarczyk

Sperzyński

et al. 2021

Sensors

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This article is devoted to the novel method of upper limb rehabilitation support using a dedicated mechatronic system. The mechatronic rehabilitation system’s main advantages are the repeatability of the process and the ability to measure key features and the progress of the therapy. In addition, the assisted therapy standard is the same for each patient. The new method proposed in this article is based on the prediction of the patient’s intentions, understood as the intentions to perform a movement that would be not normally possible due to the patient’s limited motor functions. Determining those intentions is realized based on a comparative analysis of measured kinematic (range of motion, angular velocities, and accelerations) and dynamic parameter values, as well as external loads resulting from the interaction of patients. Appropriate procedures were implemented in the control system, for which verification was conducted via experiments. The aim of the research in the article was to examine whether it is possible to sense the movement intentions of a patient during exercises, using only measured load parameters and kinematic parameters of the movement. In this study, the construction of a mechatronic system prototype equipped with sensory grip to measure the external loads, control algorithms, and the description of experimental studies were presented. The experimental studies of the mechanism were aimed at the verification of the proper operation of the system and were not a clinical trial.

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“…Firstly, the sensors are usually made of stiff materials leading to the loss of touch sensation by the user. Secondly, current sensors do not enable good sensor to skin attachment making the sensor more sensitive to unwanted movements caused by the external forces [4]. Additive manufacturing, or 3Dprinting, can overcome these difficulties due to design freedom, customisability and availability of soft materials.…”

Section: Introductionmentioning

confidence: 99%

A flexible, three material, 3D-printed, shear force sensor for use on finger tips

2019

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This paper shows the development and characterization of a 3D-printed flexible finger tip sensor that measures both shear and normal forces. The sensor is fabricated using three material fused deposition modelling (FDM) 3D-printing. The sensing principle is based on the mechanical deformation of the finger tips caused by normal and shear-forces. Therefore, the sensor is flexible and can measure the interaction forces between the environment and the finger tips, while keeping the loss of touch sensation low. Characterization shows the sensor is capable of distinguishing between normal and a shear-force components.

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Identification of Object Dynamics Using Hand Worn Motion and Force Sensors

Cited by 13 publications

References 27 publications

A Tangible Solution for Hand Motion Tracking in Clinical Applications

A Tangible Solution for Hand Motion Tracking in Clinical Applications

Prediction of Motion Intentions as a Novel Method of Upper Limb Rehabilitation Support

A flexible, three material, 3D-printed, shear force sensor for use on finger tips

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