Noninvasive determination of fiber orientation and tracking 2-dimensional deformation of human skin utilizing spatially resolved reflectance of infrared light measurement in vivo

Cha, Jaekwang; Kim, Jinhyuk; Kim, Shiho

doi:10.1016/j.measurement.2019.04.065

Cited by 8 publications

(8 citation statements)

References 17 publications

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“… Principles of sensing: six sensor modules were used, each consisting of an IR emitter and receiver. Because the change in the scattered IR intensity due to the contraction and relaxation of the skin can be expressed as a function of the distance between the sensors [ 22 ], the degree of the skin contraction and relaxation can be determined based on the IR intensity; the distance between the IR sensors is fixed. …”

Section: Figurementioning

confidence: 99%

“…Moreover, an input system and a facial expression recognition system based on the same principle have been previously reported [ 19 , 20 , 21 ]. Cha et al measured the intensity change of the scattered IR intensity due to the contraction and relaxation of skin in four areas (the abdomen, cheek, forearm, and thigh areas), and expressed the results as a function of the distance between the sensors [ 22 ]. The results indicate that the propagation of IR rays into tissue can be measured for various parts of the body.…”

Section: Introductionmentioning

confidence: 99%

“…Although a device for facial expression recognition must use several sensors and IR cameras to detect movement of the entire face, in this study the number of sensors that can be attached to the interface foam of the HMD was limited to six. Cha et al expressed the IR intensity as a function of the distance between the sensors [ 22 ]. As shown in Figure 1 , the distance between the sensors in the HMD environment was fixed, and the degrees of contraction and relaxation of the skin could be measured by a sensor module composed of IR photocoupler.…”

Section: Introductionmentioning

confidence: 99%

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Hands-Free User Interface for VR Headsets Based on In Situ Facial Gesture Sensing

Kim

Cha

Kim

2020

Sensors

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The typical configuration of virtual reality (VR) devices consists of a head-mounted display (HMD) and handheld controllers. As such, these units have limited utility in tasks that require hand-free operation, such as in surgical operations or assembly works in cyberspace. We propose a user interface for a VR headset based on a wearer’s facial gestures for hands-free interaction, similar to a touch interface. By sensing and recognizing the expressions associated with the in situ intentional movements of a user’s facial muscles, we define a set of commands that combine predefined facial gestures with head movements. This is achieved by utilizing six pairs of infrared (IR) photocouplers positioned at the foam interface of an HMD. We demonstrate the usability and report on the user experience as well as the performance of the proposed command set using an experimental VR game without any additional controllers. We obtained more than 99% of recognition accuracy for each facial gesture throughout the three steps of experimental tests. The proposed input interface is a cost-effective and efficient solution that facilitates hands-free user operation of a VR headset using built-in infrared photocouplers positioned in the foam interface. The proposed system recognizes facial gestures and incorporates a hands-free user interface to HMD, which is similar to the touch-screen experience of a smartphone.

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Section: Figurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Hands-Free User Interface for VR Headsets Based on In Situ Facial Gesture Sensing

Kim

Cha

Kim

2020

Sensors

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“…“Spatially resolved” (SR) implies using the radial distance from a light incident spot [2,4,31]. Nickel et al found that “Langer ’s line” [32], which indicates the collagen fiber distribution in human skin, follows the direction of measured SRDR of skin [4], and Cha et al showed that the SRDR measured in relation to skin deformation mirrors deformation of the skin [5]. Cha et al and Kim et al applied IR diffusion reflectance to detect VR headset user’s facial expressions [33,34].…”

Section: Sensor Implementationmentioning

confidence: 99%

“…The NIR laser is focused on the region of interest (ROI) on the skin, and the camera tracks changes of IR SRDR on the skin by capturing sequential image frames of SRDR. Changes in SRDR give clues allowing detection of the facial gestures because the captured sensor data vary depending on skin deformation conditions [5].…”

Section: Introductionmentioning

confidence: 99%

Hands-Free User Interface for AR/VR Devices Exploiting Wearer’s Facial Gestures Using Unsupervised Deep Learning

Cha

Kim

2019

Sensors

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Developing a user interface (UI) suitable for headset environments is one of the challenges in the field of augmented reality (AR) technologies. This study proposes a hands-free UI for an AR headset that exploits facial gestures of the wearer to recognize user intentions. The facial gestures of the headset wearer are detected by a custom-designed sensor that detects skin deformation based on infrared diffusion characteristics of human skin. We designed a deep neural network classifier to determine the user’s intended gestures from skin-deformation data, which are exploited as user input commands for the proposed UI system. The proposed classifier is composed of a spatiotemporal autoencoder and deep embedded clustering algorithm, trained in an unsupervised manner. The UI device was embedded in a commercial AR headset, and several experiments were performed on the online sensor data to verify operation of the device. We achieved implementation of a hands-free UI for an AR headset with average accuracy of 95.4% user-command recognition, as determined through tests by participants.

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Microneedles for advanced ocular drug delivery

Glover,

Mishra,

Gade

et al. 2023

Advanced Drug Delivery Reviews

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Noninvasive determination of fiber orientation and tracking 2-dimensional deformation of human skin utilizing spatially resolved reflectance of infrared light measurement in vivo

Cited by 8 publications

References 17 publications

Hands-Free User Interface for VR Headsets Based on In Situ Facial Gesture Sensing

Hands-Free User Interface for VR Headsets Based on In Situ Facial Gesture Sensing

Hands-Free User Interface for AR/VR Devices Exploiting Wearer’s Facial Gestures Using Unsupervised Deep Learning

Microneedles for advanced ocular drug delivery

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