“…Moreover, the linear potentiometer sensor is suitable for closed hand gloves and cannot be used in open or exoskeleton-based gloves. By contrast, Othman et al demonstrated that a rotary potentiometer sensor could be used to measure finger flexion [ 42 ]. They proposed that a rotary potentiometer sensor can be placed in finger joints to measure finger displacement.…”
Recent advancements in telecommunications and the tactile Internet have paved the way for studying human senses through haptic technology. Haptic technology enables tactile sensations and control using virtual reality (VR) over a network. Researchers are developing various haptic devices to allow for real-time tactile sensation, which can be used in various industries, telesurgery, and other mission-critical operations. One of the main criteria of such devices is extremely low latency, as low as 1 ms. Although researchers are attempting to develop haptic devices with low latency, there remains a need to improve latency and robustness to hand sizes. In this paper, a low-latency haptic open glove (LLHOG) based on a rotary position sensor and min-max scaling (MMS) filter is proposed to realize immersive VR interaction. The proposed device detects finger flexion/extension and adduction/abduction motions using two position sensors located in the metacarpophalangeal (MCP) joint. The sensor data are processed using an MMS filter to enable low latency and ensure high accuracy. Moreover, the MMS filter is used to process object handling control data to enable hand motion-tracking. Its performance is evaluated in terms of accuracy, latency, and robustness to finger length variations. We achieved a very low processing delay of 145.37 s per finger and overall hand motion-tracking latency of 4ms. Moreover, we tested the proposed glove with 10 subjects and achieved an average mean absolute error (MAE) of 3.091∘ for flexion/extension, and 2.068∘ for adduction/abduction. The proposed method is therefore superior to the existing methods in terms of the above factors for immersive VR interaction.
“…Moreover, the linear potentiometer sensor is suitable for closed hand gloves and cannot be used in open or exoskeleton-based gloves. By contrast, Othman et al demonstrated that a rotary potentiometer sensor could be used to measure finger flexion [ 42 ]. They proposed that a rotary potentiometer sensor can be placed in finger joints to measure finger displacement.…”
Recent advancements in telecommunications and the tactile Internet have paved the way for studying human senses through haptic technology. Haptic technology enables tactile sensations and control using virtual reality (VR) over a network. Researchers are developing various haptic devices to allow for real-time tactile sensation, which can be used in various industries, telesurgery, and other mission-critical operations. One of the main criteria of such devices is extremely low latency, as low as 1 ms. Although researchers are attempting to develop haptic devices with low latency, there remains a need to improve latency and robustness to hand sizes. In this paper, a low-latency haptic open glove (LLHOG) based on a rotary position sensor and min-max scaling (MMS) filter is proposed to realize immersive VR interaction. The proposed device detects finger flexion/extension and adduction/abduction motions using two position sensors located in the metacarpophalangeal (MCP) joint. The sensor data are processed using an MMS filter to enable low latency and ensure high accuracy. Moreover, the MMS filter is used to process object handling control data to enable hand motion-tracking. Its performance is evaluated in terms of accuracy, latency, and robustness to finger length variations. We achieved a very low processing delay of 145.37 s per finger and overall hand motion-tracking latency of 4ms. Moreover, we tested the proposed glove with 10 subjects and achieved an average mean absolute error (MAE) of 3.091∘ for flexion/extension, and 2.068∘ for adduction/abduction. The proposed method is therefore superior to the existing methods in terms of the above factors for immersive VR interaction.
“…There are many types as shown in the literature of data glove operating devices such as rotary potentiometer [13], piezoelectric sensors [14], inertial motion sensors [15], and conductive fibers [16]. However, these types require high expense or lead a bulky size with additional sensors.…”
In virtual reality applications, such as games and training, the use of two-handed controllers to interact with virtual objects is usually supported. To reproduce the interactive sensation of holding objects of various shapes and behaviors with both hands, previous researchers have used mechanical connections or set various peripheral brakes between controllers to simulate physical changes. However, these external devices are hard to quickly adapt to for the simulation of dynamic objects, nor can they be removed to support free manipulations. This research introduces Deformation Response virtual reality Glove, which is a pair of sensor gloves. There is no physical link and users can stretch, bend, or twist flexible materials and display physical deformations on virtual objects, allowing users to perceive the difference between haptic sensation and physical sensation simply by using their hands.
“…In the second case, with inertial sensors, it facilitates the measurement (of acceleration and orientation) in the 3 axes of each finger joint [54]. It is important to highlight that there are also sensors such as goniometers, dynamometers [55], potentiometers [56] and in some cases the electromyographic signals are measured to estimate the user's movement [57], [58].…”
Introduction: This review article is the product of research on the methods, techniques and devices used in the measurement of fine motor skills of upper limbs and its respective evolution, developed at Universidad del Cauca in 2018.
Problem: Objective measurement of the evolution of upper limb motor skills in the rehabilitation processes.
Objective: To identify the conventional techniques and electronic devices used in the measurement of the evolution of upper limb motor ability.
Methodology: Four scientific databases were reviewed in addition to the Google Scholar search engine. The keywords used for the search were: "fine motor skills", "hand measurement", "hand rehabilitation"and "hand function", among others.
Results: Approximately 3840 articles related to the subject were found. When applying the exclusion criteria, the article number to be revised was reduced to 63, which were analyzed in the present review.
Conclusions: The tools applied by health professionals are convenient due to their rapid execution and easy access, however they can be subject to human error since they depend on the experience of the user. Electronic systems present objective measurements, however, their complexity and cost are high.
Originality: This work presents information on the therapeutic techniques and technological devices used, in certain pathologies, for the evaluation of upper limb motor ability.
Limitations: Not all articles analyzed have a detailed description of the people in which the studies were conducted.
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