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T. Ishikawa

Bio: T. Ishikawa is an academic researcher from Hosei University. The author has contributed to research in topics: The Internet & Heartbeat. The author has an hindex of 3, co-authored 4 publications receiving 244 citations.

Papers
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Journal ArticleDOI
TL;DR: Using the newly developed system, heartbeat, respiration, apnea, snoring and body movements are clearly measured and the optimal signal-to-noise (S/N) ratio by which to evaluate the reliability of the heart rate measurement is presented.
Abstract: We have developed a noninvasive pneumatics-based system by which to measure heartbeat, respiration, snoring, and body movements of a subject in bed. A thin, air-sealed cushion is placed under the bed mattress of the subject and the small movements attributable to human automatic vital functions are measured as changes in pressure using a pressure sensor having an almost flat frequency response from 0.1 to 5 kHz and a sensitivity of 56 mV/Pa. Using the newly developed system, heartbeat, respiration, apnea, snoring and body movements are clearly measured. In addition, the optimal signal-to-noise (S/N) ratio by which to evaluate the reliability of the heart rate measurement is presented. Heart rates were measured for four different body postures, 13 different subjects, four different bed mattresses, and three different sensor positions. For these measurements, the S/N ratios ranged from 15.9 to 23.5 dB, and so were determined to be reliable.

235 citations

Proceedings ArticleDOI
H. Andoh1, T. Ishikawa1, Kazuyuki Kobayashi1, Kajiro Watanabe1, T. Nakamura1 
01 Jan 2003
TL;DR: A development of health monitoring system that uses a non-invasive type microphone based pressure sensor that can estimate the sleep stages from the heartbeats and body motion measured by the sensor is described.
Abstract: This paper describes a development of health monitoring system that uses a non-invasive type microphone based pressure sensor The system can estimate the sleep stages from the heartbeats and body motion measured by the sensor The algorithm for sleep stages estimations as implemented to the single chip microcomputer The validity of the proposed system is confirmed by comparing the conventional sleep stage estimation results

16 citations

Proceedings Article
01 Jan 2003
TL;DR: A new automatic sleep stage judgment system was proposed using a non-invasive type air mattress sensor enabling the detection of three useful bio-signals: heartbeat rate, respiratory rate and other body movement, which developed a novel sleep estimation method free from any stress.
Abstract: In this study, a new automatic sleep stage judgment system was proposed using a non-invasive type air mattress sensor enabling the detection of three useful bio-signals: heartbeat rate, respiratory rate and other body movement We found that fairly good correlations exist between these signals and the sleep stage Based on this knowledge, we developed a novel sleep estimation method free from any stress

4 citations

Proceedings Article
01 Jan 2003
TL;DR: In this paper, the difference between users' watching areas for a given Web site was analyzed using an eye-mark recorder measuring viewpoint behavior, which was used to analyze users' viewing areas.
Abstract: For Internet advertisements, it is important to know which area of the screen is most suitable for contents to be easily recognized by users. The purpose of this study was to analyze the difference between users' watching areas for a given Web site. In order to analyze users' viewing areas, we used an eye-mark recorder measuring viewpoint behavior.

Cited by
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Journal ArticleDOI
TL;DR: The emergence of `ambient-assisted living’ (AAL) tools for older adults based on ambient intelligence paradigm is summarized and the state-of-the-art AAL technologies, tools, and techniques are summarized.
Abstract: In recent years, we have witnessed a rapid surge in assisted living technologies due to a rapidly aging society. The aging population, the increasing cost of formal health care, the caregiver burden, and the importance that the individuals place on living independently, all motivate development of innovative-assisted living technologies for safe and independent aging. In this survey, we will summarize the emergence of `ambient-assisted living” (AAL) tools for older adults based on ambient intelligence paradigm. We will summarize the state-of-the-art AAL technologies, tools, and techniques, and we will look at current and future challenges.

1,000 citations

Journal ArticleDOI
01 Dec 2013
TL;DR: The state-of-the-art artificial intelligence (AI) methodologies used for developing AmI system in the healthcare domain are summarized, including various learning techniques (for learning from user interaction), reasoning techniques ( for reasoning about users' goals and intensions), and planning techniques (For planning activities and interactions).
Abstract: Ambient Intelligence (AmI) is a new paradigm in information technology aimed at empowering people's capabilities by means of digital environments that are sensitive, adaptive, and responsive to human needs, habits, gestures, and emotions. This futuristic vision of daily environment will enable innovative human-machine interactions characterized by pervasive, unobtrusive, and anticipatory communications. Such innovative interaction paradigms make AmI technology a suitable candidate for developing various real life solutions, including in the healthcare domain. This survey will discuss the emergence of AmI techniques in the healthcare domain, in order to provide the research community with the necessary background. We will examine the infrastructure and technology required for achieving the vision of AmI, such as smart environments and wearable medical devices. We will summarize the state-of-the-art artificial intelligence (AI) methodologies used for developing AmI system in the healthcare domain, including various learning techniques (for learning from user interaction), reasoning techniques (for reasoning about users' goals and intensions), and planning techniques (for planning activities and interactions). We will also discuss how AmI technology might support people affected by various physical or mental disabilities or chronic disease. Finally, we will point to some of the successful case studies in the area and we will look at the current and future challenges to draw upon the possible future research paths.

565 citations

Journal ArticleDOI
01 Jul 2015
TL;DR: The recent advances in modern BCG and SCG research are reviewed, including reduced measurement noise, clinically relevant feature extraction, and signal modeling.
Abstract: In the past decade, there has been a resurgence in the field of unobtrusive cardiomechanical assessment, through advancing methods for measuring and interpreting ballistocardiogram (BCG) and seismocardiogram (SCG) signals. Novel instrumentation solutions have enabled BCG and SCG measurement outside of clinical settings, in the home, in the field, and even in microgravity. Customized signal processing algorithms have led to reduced measurement noise, clinically relevant feature extraction, and signal modeling. Finally, human subjects physiology studies have been conducted using these novel instruments and signal processing tools with promising results. This paper reviews the recent advances in these areas of modern BCG and SCG research.

558 citations

Journal ArticleDOI
TL;DR: The main aim is to review current state of the art monitoring systems and to perform extensive and an in-depth analysis of the findings in the area of smart health monitoring systems.
Abstract: Health monitoring systems have rapidly evolved during the past two decades and have the potential to change the way health care is currently delivered. Although smart health monitoring systems automate patient monitoring tasks and, thereby improve the patient workflow management, their efficiency in clinical settings is still debatable. This paper presents a review of smart health monitoring systems and an overview of their design and modeling. Furthermore, a critical analysis of the efficiency, clinical acceptability, strategies and recommendations on improving current health monitoring systems will be presented. The main aim is to review current state of the art monitoring systems and to perform extensive and an in-depth analysis of the findings in the area of smart health monitoring systems. In order to achieve this, over fifty different monitoring systems have been selected, categorized, classified and compared. Finally, major advances in the system design level have been discussed, current issues facing health care providers, as well as the potential challenges to health monitoring field will be identified and compared to other similar systems.

330 citations

Journal ArticleDOI
TL;DR: A comparative review of the two conventional methods, electrocardiogram (ECG) and photoplethysmography (PPG), and the novel methods of non-contact measuring of HR with capacitively coupled ECG, Doppler radar, optical vibrocardiography, thermal imaging, RGB camera and HR from speech.

248 citations