Applications of the PowerGlove for Measurement of Finger Kinematics

Noort, Josien C. van den; Dijk, Kees van; Kortier, H.G.; Beek, Nathalie van; Verhagen, Rens; Bour, L.J.; Veltink, Petrus H.

doi:10.1109/bsn.workshops.2014.19

Cited by 4 publications

(3 citation statements)

References 9 publications

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“…The software allows to set the sampling period and to select the number of sensors needed for measurement. Often a single accelerometer is enough for tremor monitoring, sometimes three or more accelerometers are needed, for example, in the evaluation of the hand tremor [17], [18]. The device is equipped with a long-life battery (3.8 V, 5.1 Ah) so that it can be used to monitor patients outdoor.…”

Section: Fig 1 Block Diagram Of the Monitoring Systemmentioning

confidence: 99%

A Movement-Tremors Recorder for Patients of Neurodegenerative Diseases

Gugliandolo

Campobello

Capra

et al. 2019

IEEE Trans. Instrum. Meas.

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Neurodegenerative diseases such as Alzheimer, Parkinson, motor neuron, and Chorea affect millions of people today. Their effect on the central nervous system causes the loss of brain functions as well as motor disturbances and sometimes cognitive deficits. In such a scenario, the monitoring and evaluation of early symptoms are mandatory for the improvement of the patient's quality of life. Here, the authors describe the development, the laboratory calibration, and the "in-field validation" under the medical supervision of a movement tremors recorder for subjects affected by neurodegenerative diseases. The developed device is based on an array of four accelerometers connected to an embedded development board. This system is able to monitor tremor/movement, accidental falls, and, moreover, it can track the Alzheimer subjects' geographical position. A remote supervisor can collect data from the system through Bluetooth, Wi-Fi, or GSM connections. A data compression algorithm was developed directly on board in order to increase the efficiency of data transmission and reduce power consumptions.

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Section: Fig 1 Block Diagram Of the Monitoring Systemmentioning

confidence: 99%

A Movement-Tremors Recorder for Patients of Neurodegenerative Diseases

Gugliandolo

Campobello

Capra

et al. 2019

IEEE Trans. Instrum. Meas.

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“…For measuring forces on a fingertip, a finger cap which fixates the force sensor on the fingertip is designed using 3D printing. Currently, experiments are performed with a glove with motion sensors [32,33] to track the finger and hand movement. In the near future this system will be integrated with the force sensor presented here, to estimate the mechanical power transferred during a given procedure.…”

Section: Packaging and Applicationmentioning

confidence: 99%

Miniature large range multi-axis force-torque sensor for biomechanical applications

Brookhuis¹,

Sanders²,

Ma³

et al. 2015

J. Micromech. Microeng.

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A miniature force sensor for the measurement of forces and moments at a human fingertip is designed and realized. Thin silicon pillars inside the sensor provide in-plane guidance for shear force measurement and provide the spring constant in normal direction. A corrugated silicon ring around the force sensitive area provides the spring constant in shear direction and seals the interior of the sensor. To detect all load components, capacitive read-out is used. A novel electrode pattern results in a large shear force sensitivity. The fingertip force sensor has a wide force range of up to 60 N in normal direction, ± 30 N in shear direction and a torque range of ± 25 N mm.

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“…In this thesis, we have focused on the development of a system for clinical measurement purposes [132] which requires accurate and reliable full 3D pose estimates of different fingers and the hand in an unobtrusive manner.…”

Section: Discussion and Outlookmentioning

confidence: 99%

Assessment of hand kinematics and interactions with the environment

Kortier¹

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The hand is one of the most important instruments of our body. Its versatility enables the execution of a wide range of tasks that ask for a powerful, precise or gentle approach. Measuring hand and finger movements, and interaction forces, is therefore important for the assessment of tasks in daily life. However, measuring on-body kinematic and kinetic quantities is a delicate procedure due to the dexterity of the hand, and moreover, the little and complex shaped skin places for sensor attachment. This thesis proposes a new on-body assessment system that allows the measurement of movements and interaction forces of the hand, fingers and thumb.The first objective, the development, evaluation and validation of an inertial and magnetic sensing system for the measurement of hand and finger kinematics is the topic of chapters 2 to 5. The second objective, assessment of the dynamic interaction between human hand and environment using combined force and movement sensing, is the topic of chapter 6.Chapter 2 describes the hardware and algorithms for a sensing system which can be attached to the hand, fingers and the thumb. The hardware consists of multiple inertial and magnetic sensors to measure angular velocities, accelerations and the magnetic field. Each individual finger and the thumb is modelled as a kinematic chain where the bones correspond to the linkages and each joint is considered as an ideal ball-socket joint. Segmental lengths were determined by manual measurement, whereas the inertial sensors provided the input for a Kalman filter to estimate the 3D orientation of the corresponding segment. Hereafter, the orientation and tip position of each finger was estimated by applying forward kinematics. To our knowledge, it is the first system that uses inertial sensors for estimating finger kinematics. The estimation quality was expressed in terms of static and dynamic accuracy, dynamic range and repeatability. Differences with an active optical reference system were found to be a maximum of 13 mm for the finger tip distance difference during circular pointing movements. A standardized test protocol for instrumented gloves showed very good repeatability results compared to other datagloves, proven by the mean angle difference of < 2 degrees. Finally, a dynamic range was specified as a measure of how well the system is able to reconstruct joint angles when experiencing large angular velocities. The system showed accurate reconstruction up to 116 full index finger flex-extension movements per minute.Chapter 3 reports an extensive comparison of our inertial sensing system against a passive opto-electronic marker system. It aims on typical hand-function tasks, including tapping, (fast) finger flexion, hand opening/closing, ab-adduction and circular pointing, which are used to quantify various motor symptoms for clinical diagnosis. Three subjects were included and instrumented with both systems. Differences in position, Range of Motion (RoM) and 3D vii joint angles were noted of which the largest were found in fast and ...

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Applications of the PowerGlove for Measurement of Finger Kinematics

Cited by 4 publications

References 9 publications

A Movement-Tremors Recorder for Patients of Neurodegenerative Diseases

A Movement-Tremors Recorder for Patients of Neurodegenerative Diseases

Miniature large range multi-axis force-torque sensor for biomechanical applications

Assessment of hand kinematics and interactions with the environment

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