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      Development, fabrication and evaluation of passive interface gloves

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          Abstract

          Previously, glove-integrated communication based on gestures, hand movement and finger touch had a complex operating system and an active power source was needed. This paper introduces batteryless and maintenance-free interface gloves. Our solution is based on passive ultra-high frequency (UHF) radio frequency identification (RFID) technology, comprising four electro-textile antenna parts and three RFID microchips (each with a unique ID). The three RFID microchips have unique IDs, which can be activated by the gentle touch of the human finger and used to control the surrounding technology. The aim is to evaluate the reliability of different conductive materials and microchip attachment methods. The antennas are fabricated from two different materials: a stretchable and a non-stretchable commercial electro-textile. Further, two types of microchip attachment methods are used with both antenna materials: a conductive silver epoxy and embroidery with conductive multifilament silver-plated thread. The developed interface gloves are tested by six users in a home and in an office environment, where they achieve 93–100% success rates. Especially those glove interfaces with the antennas fabricated from the non-stretchable electro-textile and the antenna-microchip interconnections embroidered with conductive thread showed good read ranges (80–110 cm). The gloves also show practical functionality, when tested with a mobile reader in practical identification and access control application. These results are very encouraging, especially when considering that the interface glove, being maintenance-free and cost-effective, promises versatile and interesting applications for customizing user-friendly augmentative and alternative communication solutions, easy controlling of ambient assisted-living applications, and providing simple identification and access control for increased safety and comfort.

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          Most cited references25

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          Sign-to-speech translation using machine-learning-assisted stretchable sensor arrays

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            Brain-computer interface in paralysis.

            Communication with patients suffering from locked-in syndrome and other forms of paralysis is an unsolved challenge. Movement restoration for patients with chronic stroke or other brain damage also remains a therapeutic problem and available treatments do not offer significant improvements. This review considers recent research in brain-computer interfaces (BCIs) as promising solutions to these challenges. Experimentation with nonhuman primates suggests that intentional goal directed movements of the upper limbs can be reconstructed and transmitted to external manipulandum or robotic devices controlled from a relatively small number of microelectrodes implanted into movement-relevant brain areas after some training, opening the door for the development of BCI or brain-machine interfaces in humans. Although noninvasive BCIs using electroencephalographic recordings or event-related-brain-potentials in healthy individuals and patients with amyotrophic lateral sclerosis or stroke can transmit up to 80 bits/min of information, the use of BCIs - invasive or noninvasive - in severely or totally paralyzed patients has met some unforeseen difficulties. Invasive and noninvasive BCIs using recordings from nerve cells, large neuronal pools such as electrocorticogram and electroencephalography, or blood flow based measures such as functional magnetic resonance imaging and near-infrared spectroscopy show potential for communication in locked-in syndrome and movement restoration in chronic stroke, but controlled phase III clinical trials with larger populations of severely disturbed patients are urgently needed.
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              Brain-machine interface (BMI) in paralysis.

              Brain-machine interfaces (BMIs) use brain activity to control external devices, facilitating paralyzed patients to interact with the environment. In this review, we focus on the current advances of non-invasive BMIs for communication in patients with amyotrophic lateral sclerosis (ALS) and for restoration of motor impairment after severe stroke.
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                Author and article information

                Contributors
                (View ORCID Profile)
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                Journal
                Textile Research Journal
                Textile Research Journal
                SAGE Publications
                0040-5175
                1746-7748
                December 2021
                June 02 2021
                December 2021
                : 91
                : 23-24
                : 3023-3032
                Affiliations
                [1 ]Tampere University - Hervanta Campus, Tampere, Finland
                Article
                10.1177/00405175211019132
                c8467fcd-fd2f-48a0-8c32-11b1815bfe54
                © 2021

                https://creativecommons.org/licenses/by/4.0/

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