• Title/Summary/Keyword: Mobile healthcare device

Search Result 74, Processing Time 0.018 seconds

Implementation and Evaluation of ECG Authentication System Using Wearable Device (웨어러블 디바이스를 활용한 ECG 인증 시스템 구현 및 평가)

  • Heo, Jae-Wook;Jin, Sun-Woo;Jun, Moon-Seog
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.20 no.10
    • /
    • pp.1-6
    • /
    • 2019
  • As mobile technologies such as Internet of Things (IoT)-based smart homes and financial technologies (FinTech) are developed, authentication by smart devices is used everywhere. As a result, presence-based biometric authentication using smart devices has become a new mainstream in knowledge-based authentication methods like the existing passwords. The electrocardiogram (ECG) is less prone to forgery, and high-level personal identification is its unique feature from among various biometric authentication methods, such as the pulse, fingerprints, the face, and the iris. Biometric authentication using an ECG is receiving a great deal of attention due to its uses in healthcare and FinTech. In this study, we implemented an ECG authentication system that allows users to easily measure and authenticate their ECG waveforms using a miniaturized wearable device, rather than a large and expensive measurement device. The implemented ECG authentication system identifies ECG features through P-Q-R-S-T feature point identification, and was user-certified under the proposed authentication protocols. Finally, assessment of measurements in a majority of adult males showed a relatively low false acceptance rate of 1.73%, and a low false rejection rate of 4.14%, in a stable normal state. In a high-activity state, the false acceptance rate was 13.72%, and the false rejection rate was 21.68%. In a high-heart rate state, the false acceptance rate was 10.48%, and the false rejection rate was 11.21%.

Recent Progress in Micro In-Mold Process Technologies and Their Applications (마이크로 인몰드 공정기술 기반 전자소자 제조 및 응용)

  • Sung Hyun Kim;Young Woo Kwon;Suck Won Hong
    • Journal of the Microelectronics and Packaging Society
    • /
    • v.30 no.2
    • /
    • pp.1-12
    • /
    • 2023
  • In the current era of the global mobile smart device revolution, electronic devices are required in all spaces that people interact with. The establishment of the internet of things (IoT) among smart devices has been recognized as a crucial objective to advance towards creating a comfortable and sustainable future society. In-mold electronic (IME) processes have gained significant industrial significance due to their ability to utilize conventional high-volume methods, which involve printing functional inks on 2D substrates, thermoforming them into 3D shapes, and injection-molded, manufacturing low-cost, lightweight, and functional components or devices. In this article, we provide an overview of IME and its latest advances in application. We review biomimetic nanomaterials for constructing self-supporting biosensor electronic materials on the body, energy storage devices, self-powered devices, and bio-monitoring technology from the perspective of in-mold electronic devices. We anticipate that IME device technology will play a critical role in establishing a human-machine interface (HMI) by converging with the rapidly growing flexible printed electronics technology, which is an integral component of the fourth industrial revolution.

Study on the Smart 1RM System Development and Effect Verification for Health Improvement and Management of National Healthcare (국민 건강관리 및 체력증진을 위한 스마트 1RM 시스템 개발 및 효과 검증에 관한 연구)

  • Woo, Kyung-Min;Shin, Mi-Yeon;Yu, Chang-Ho
    • Journal of rehabilitation welfare engineering & assistive technology
    • /
    • v.12 no.1
    • /
    • pp.53-62
    • /
    • 2018
  • In this study, we developed a smart 1RM system for national health management and physical fitness, which enables quantitative 1RM measurement in various types of exercise using digital pulley technology, and to test the effect on training by using it. We developed the smart 1RM system, which is composed of portable muscle strength measuring device, Bluetooth communication based mobile phone data transmission and circuit diagram, and height adjustable system body. We recruited the 30 participants with 20th aged and divided into training and non-performing groups with 15 participants randomly. The participants performed 5 sets of elbow, lumbar, knee extension / flexion 10 times using smart 1RM system and the experimental period was 3 days a week for a total of 8 weeks. The experimental results showed that the maximum strength of the elbow, lumbar, and knee joints was significantly improved before and after maximal muscle strength training in the training group. Oxygen intakes during 1RM exercise mode showed 10.91% than endurance. To verify the validity of the smart 1RM maximal strength data, the reliability was 0.895 (* p <0.00). This study can be applied to the early rehabilitation treatment of the elderly and rehabilitation patients more quantitatively using the national health care.

Smartphone vs Wearable, Finding the Correction Factor for the Actual Step Count - Based on the In-situ User Behavior of the Two Devices - (스마트폰 vs 웨어러블, 실제 걸음 수 산출을 위한 보정계수의 발견 - 두 기기의 In-situ 활용 행태 비교를 바탕으로 -)

  • Han, Sang Kyu;Kim, Yoo Jung;An, A Ju;Heo, Eun Young;Kim, Jeong Whun;Lee, Joong Seek
    • Design Convergence Study
    • /
    • v.16 no.6
    • /
    • pp.123-135
    • /
    • 2017
  • In recent mobile health care service, health management using number of steps is becoming popular. In addition, a variety of activity trackers have made it possible to measure the number of steps more accurately and easily. Nevertheless, the activity tracker is not popularized, and it is a trend to use the pedometer sensor of the smartphone as an alternative. In this study, we tried to find out how much the number of steps collected by the smartphone versus the actual number of steps in actual situations, and what factors make the difference. We conducted an experiment to collect number of steps data of 21 people using the smartphone and wearable device simultaneously for 7 days. As a result, we found that the average number of steps of the smartphone is 62% compared to the actual number of steps, and that there is a large variation among users. We derived a regression model in which the accuracy of smartphone increases with the degree of awareness of smartphone. We expect that this can be used as a factor to correct the difference from the actual number of steps in the smartphone alone healthcare service.