Self‐Powered Smart Gloves Based on Triboelectric Nanogenerators

Abstract

movement recognition systems which can turn these movements into analyzable data that can be further used to integrate technology into daily life and improve it.In the United States, approximately 15% of the adult population report some form of hearing loss, [6] and thus rely on sign language to communicate. However, most of the hearing population are not fluent in sign language, creating a barrier in communication between the deaf and hearing communities. To further complicate the issue, different languages and countries have different sign languages. For example, although an English speaker suffers no language barrier in both the United States and United Kingdom, American Sign Language signers may have difficulty understanding British Sign Language. [7] Currently, many devices have been created for purpose of gesture recognition and can be either vision-based or sensor-based. [8] Vision-based devices can record images or videos in either 2D, through a single camera, [9][10][11][12][13] or in 3D, through stereo cameras [14][15][16] or light projection methods. [17][18][19] Next, they distinguish the hand from the background through methods such as include skin color detection, [20][21][22] using a unique background, [23,24] and entropy measurement by subtracting successive images. [25,26] As these devices are heavily light and background dependent, they do not work when in dim lighting, if the skin color of the user is similar to that of the background, or if fingers are overlapping. On the other hand, sensor-based devices use sensors, rather than cameras, to measure changes in hand and finger movements. The most common method of doing so is using sensing gloves that contain flex and IMU sensors to determine the orientation, acceleration, and bending angle of the hands and fingers. [27][28][29][30][31] Another method of sensor-based gesture recognition is through electromyography, which can record the muscle tissue activity using multiple electrodes placed on the skin, [32][33][34][35][36] but may impede movement and be uncomfortable for the user. Wireless signals and radar can also be used to measure gestures, [37][38][39] but suffer from limitations such as signal strength and difficulties in distinguishing hand gestures from different people. In addition to the aforementioned disadvantages, a common issue with both vision and sensor-based gesture recognition methods are that they are not self-powered, which means that they are unable to be used continuously throughout the day. These problems pose major disadvantages for those who are deaf or hard-of-hearing, proving the need for a comfortable, universal, and accurateThe hands are used in all facets of daily life, from simple tasks such as grasping and holding to complex tasks such as communication and using technology. Finding a way to not only monitor hand movements and gestures but also to integrate that data with technology is thus a worthwhile task. Gesture recognition is particularly important for those who rely on sign language to communicate, but the l...

Advances in Wearable Strain Sensors Based on Electrospun Fibers

“…[288][289][290][291][292][293][294][295] For example, integrating nano-generators in fabrics to become self-powered wearable devices, which cause mechanical friction and deformation through body movements, and then convert mechanical energy triggered by biomechanical movements into electrical energy for supplying sensors. [286,[296][297][298][299][300][301][302][303][304][305] The uninterrupted chest movement during human breathing can be used as continuous biokinetic energy to drive low-power wearable electronic devices. [57,306] In addition, one or more of body heat, body fluids, and solar irradiance can also be harvested and converted to drive sensors.…”

Triboelectric nanogenerators enhanced by a metal–organic framework for sustainable power generation and air mouse technology

“…The mechano-electric sensing ability of the TENG leads to various smart applications. Some smart applications are touchpads, 32 smart gloves, 33 smart helmets, 34 respiratory sensors, 35 and wireless transmission 36 sweat monitoring. 37 Future technology is based on an air mouse or air keyboard without touch.…”

InMyFace: Inertial and mechanomyography-based sensor fusion for wearable facial activity recognition

“…We can find several textile-based sensing modalities on gloves for drone control in the literature. Researchers have employed various sensing technologies, including textile pressure sensors, triboelectric nanogenerators (TENG), flexible capacitive pressure sensors, piezoresistive sensors, and conductive fiber-based textile pressure sensors, among others [1,10,18,20]. A common practice among state-of-the-art textile wearable glove alternatives is to use different and limited gesture dictionaries compared to camera-based solutions, mainly including going forward/backward and going to the left/right classes.…”

“…However, this solution does not account for the potential extension of gestures by including both hands in the pipeline. In [18], the authors used TENG to fabricate a sensing glove for gesture recognition, including sign language and drone control applications. However, their focus was mainly on introducing the technology and its futuristic applications, thus neglecting null activities and lacking information about user experimental evaluations.…”