Clothing-integrated RFID-based Interface for Human-Technology Interaction

Mehmood, Adnan; Qureshi, Shoaib; He, Han; Chen, Xiaochen; Ahmed, Shahbaz; Merilampi, Sari; Raumonen, Pasi; Ukkonen, Leena; Virkki, Johanna

doi:10.1109/segah.2019.8882467

Cited by 9 publications

(5 citation statements)

References 10 publications

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“…Conductive fabrics can either be made of conductive fibers or consist of a thin metal layer deposited on top of the textile surface. Laser-structured Ni/Cu and Sn/Cu plated textile have been ironed onto the fabric without affecting significantly the properties of the textile ( Mehmood et al., 2019 ), ( Buechley and Eisenberg, 2009 ). Rotzler et al.…”

Section: Electronics System Integration On Textilesmentioning

confidence: 99%

Toward autonomous wearable triboelectric systems integrated on textiles

Gaubert¹,

Vauche²,

Weimmerskirch-Aubatin³

et al. 2022

iScience

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Section: Electronics System Integration On Textilesmentioning

confidence: 99%

Toward autonomous wearable triboelectric systems integrated on textiles

Gaubert¹,

Vauche²,

Weimmerskirch-Aubatin³

et al. 2022

iScience

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“…A graphical user interface plots them on a body diagram, simplifying collecting information on focal patient complaints and problems. In this approach, through a body user interface (some body-UIs are designed for healthcare applications and help monitor patients' primary health parameters 70 ). The collection of patient complaints and problems is obtained.…”

Section: Data Gathering and Processingmentioning

confidence: 99%

“…It is easy to access databases of patients' past diseases use medicines, instructions, and protocols to support the emergency medical technician. In recent research, 69,70 a graphical user interface was developed to handle coronavirus pandemics in the medical research community. In Figure 7, we illustrated the data gathering process used.…”

Section: Data Gathering and Processingmentioning

confidence: 99%

Deep learning: A taxonomy of modern weapons to combat Covid‐19 similar pandemics in smart cities

Saeedvand

Jafari

Aghdasi

et al. 2022

Concurrency and Computation

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Summary The Covid‐19 pandemic has affected many lives over the past year. In addition to the enormous health cost, the necessary lockdowns and government‐mandated suspension to prevent the spread of the virus had a huge economic impact. The new challenges in 2021 were combating new virus mutations and providing effective vaccines globally. Artificial intelligent (AI) and machine learning have made significant improvements in many different applications during the last decades. One of the advanced and robust technologies in machine learning is deep learning (DL), which can be employed to help prevent initial infections and detect and monitor their progress and side effects. Fast and accurate Covid‐19 infection detection and treatment of suspected patients is essential to make better decisions, ensure treatment, and even save patients' lives. Modern technologies are required to achieve these objectives and create a sustainable society. This article presents a taxonomy in DL algorithms to cover both the technical novelties and empirical results techniques for Covid‐19 in smart cities. In this regard, (i) we demonstrate possible DL algorithms capable of combating Covid‐19; (ii) we propose an up‐to‐date perspective of DL algorithms in social prevention and medical treatment; and (iii) we identify the challenges in combating Covid‐19 outbreaks.

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“…e antenna design is based on our previous paper [43], where we introduced a wrist antenna that had antenna bands going around the wrist. e idea of these antenna bands is that the human wrist will not fully cover the antenna.…”

Section: Platform Design and Fabricationmentioning

confidence: 99%

“…Due to the unique ID of each IC, these components can be then used as specific input buttons. Our first passive RFID-based human-technology interaction solution was based on a shirtintegrated antenna, which could be used to activate single RFID IC components placed around the user [43]. Next, we further developed this concept of integrating RFID ICs in the environment around us, by installing a passive RFID-based platform, consisting of three RFID ICs on the surface of the wooden table [44].…”

Section: Introductionmentioning

confidence: 99%

ClothFace: A Passive RFID-Based Human-Technology Interface on a Shirtsleeve

Mehmood

Chen

et al. 2020

Advances in Human-Computer Interaction

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This paper introduces ClothFace, a shirtsleeve-integrated human-technology interface platform, which comprises two wrist antennas and three radio frequency identification (RFID) integrated circuits (ICs), each with a unique ID. The platform prototype, which is created on a shirtsleeve by cutting the antennas and antenna-IC interconnections from copper tape, can be used for push button and swipe controlling. Each IC can be activated, i.e., electrically connected to the two antennas, by touching the IC. These ICs can act as wireless input buttons to the technology around us. Due to the used passive ultrahigh-frequency (UHF) RFID technology, there is no need for clothing-integrated energy sources, but the interface platform gets all the needed energy from an external RFID reader. The platform prototype was found to be readable with an external RFID reader from all directions at distances of 70–80 cm. Further, seven people giving altogether 1400 inputs tested the prototype sleeves on a table and on body. In these first tests, 96–100% (table) and 92–100% (on-body) success rates were achieved in a gamelike testing setup. Further, the platform was proved to be readable with an off-the-shelf handheld RFID reader from a distance of 40 cm. Based on these initial results, this implementation holds the potential to be used as a touch interface blended into daily clothing, as well as a modular touch-based interaction platform that can be integrated into the surfaces of electronic devices, such as home appliances.

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Clothing-integrated RFID-based Interface for Human-Technology Interaction

Cited by 9 publications

References 10 publications

Toward autonomous wearable triboelectric systems integrated on textiles

Toward autonomous wearable triboelectric systems integrated on textiles

Deep learning: A taxonomy of modern weapons to combat Covid‐19 similar pandemics in smart cities

ClothFace: A Passive RFID-Based Human-Technology Interface on a Shirtsleeve

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