Daniel Teichmann

Bio: Daniel Teichmann is an academic researcher from RWTH Aachen University. The author has contributed to research in topics: Capacitive sensing & Eddy current. The author has an hindex of 13, co-authored 55 publications receiving 618 citations. Previous affiliations of Daniel Teichmann include Massachusetts Institute of Technology & University of Southern Denmark.

Unobtrusive vital sign monitoring in automotive environments-a review

Abstract: This review provides an overview of unobtrusive monitoring techniques that could be used to monitor some of the human vital signs (i.e., heart activity, breathing activity, temperature and potentially oxygen saturation) in a car seat. It will be shown that many techniques actually measure mechanical displacement, either on the body surface and/or inside the body. However, there are also techniques like capacitive electrocardiogram or bioimpedance that reflect electrical activity or passive electrical properties or thermal properties (infrared thermography). In addition, photopleythysmographic methods depend on optical properties (like scattering and absorption) of biological tissues and—mainly—blood. As all unobtrusive sensing modalities are always fragile and at risk of being contaminated by disturbances (like motion, rapidly changing environmental conditions, triboelectricity), the scope of the paper includes a survey on redundant sensor arrangements. Finally, this review also provides an overview of automotive demonstrators for vital sign monitoring.

The MAIN Shirt: a textile-integrated magnetic induction sensor array.

Abstract: A system is presented for long-term monitoring of respiration and pulse. It comprises four non-contact sensors based on magnetic eddy current induction that are textile-integrated into a shirt. The sensors are technically characterized by laboratory experiments that investigate the sensitivity and measuring depth, as well as the mutual interaction between adjacent pairs of sensors. The ability of the device to monitor respiration and pulse is demonstrated by measurements in healthy volunteers. The proposed system (called the MAIN (magnetic induction) Shirt) does not need electrodes or any other skin contact. It is wearable, unobtrusive and can easily be integrated into an individual's daily routine. Therefore, the system appears to be a suitable option for long-term monitoring in a domestic environment or any other unsupervised telemonitoring scenario.

Noncontact Monitoring of Respiratory Rate in Newborn Infants Using Thermal Imaging

Abstract: Monitoring of respiratory rate (RR) is very important for patient assessment In fact, it is considered one of the relevant vital parameters in critical care medicine Nowadays, standard monitoring relies on obtrusive and invasive techniques, which require adhesive electrodes or sensors to be attached to the patient's body Unfortunately, these procedures cause stress, pain, and frequently damage the vulnerable skin of preterm infants This paper presents a “black-box” algorithm for remote monitoring of RR in thermal videos “Black-box” in this context means that the algorithm does not rely on tracking of specific anatomic landmarks Instead, it automatically distinguishes regions of interest in the video containing the respiratory signal from those containing only noise To examine its performance and robustness during physiological (phase A) and pathological scenarios (phase B), a study on 12 healthy volunteers was carried out After a successful validation on adults, a clinical study on eight newborn infants was conducted A good agreement between estimated RR and ground truth was achieved In the study involving adult volunteers, a mean root-mean-square error (RMSE) of ( $031 \pm 009$ ) breaths/min and ( $327 \pm 072$ ) breaths/min was obtained for phase A and phase B, respectively In the study involving infants, the mean RMSE hovered around ( $415 \pm 144$ ) breaths/min In brief, this paper demonstrates that infrared thermography might become a clinically relevant alternative for the currently available RR monitoring modalities in neonatal care

Noncontact Monitoring of Cardiorespiratory Activity by Electromagnetic Coupling

Abstract: In this paper, the method of noncontact monitoring of cardiorespiratory activity by electromagnetic coupling with human tissue is investigated. Two measurement modalities were joined: an inductive coupling sensor based on magnetic eddy current induction and a capacitive coupling sensor based on displacement current induction. The system's sensitivity to electric tissue properties and its dependence on motion are analyzed theoretically as well as experimentally for the inductive and capacitive coupling path. The potential of both coupling methods to assess respiration and pulse without contact and a minimum of thoracic wall motion was verified by laboratory experiments. The demonstrator was embedded in a chair to enable recording from the back part of the thorax.

A Bendable and Wearable Cardiorespiratory Monitoring Device Fusing Two Noncontact Sensor Principles

Abstract: A mobile device is presented for monitoring both respiration and pulse. The device is developed as a bendable/flexible inlay that can be placed in a shirt pocket or the inside pocket of a jacket. To achieve optimum monitoring performance, the device combines two sensor principles, which work in a safe noncontact way through several layers of cotton or other textiles. One sensor, based on magnetic induction, is intended for respiratory monitoring, and the other is a reflective photoplethysmography sensor intended for pulse detection. Because each sensor signal has some dependence on both physiological parameters, fusing the sensor signals allows enhanced signal coverage.

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Development of Smart Healthcare Monitoring System in IoT Environment.

Abstract: Healthcare monitoring system in hospitals and many other health centers has experienced significant growth, and portable healthcare monitoring systems with emerging technologies are becoming of great concern to many countries worldwide nowadays. The advent of Internet of Things (IoT) technologies facilitates the progress of healthcare from face-to-face consulting to telemedicine. This paper proposes a smart healthcare system in IoT environment that can monitor a patient’s basic health signs as well as the room condition where the patients are now in real-time. In this system, five sensors are used to capture the data from hospital environment named heart beat sensor, body temperature sensor, room temperature sensor, CO sensor, and CO2 sensor. The error percentage of the developed scheme is within a certain limit (< 5%) for each case. The condition of the patients is conveyed via a portal to medical staff, where they can process and analyze the current situation of the patients. The developed prototype is well suited for healthcare monitoring that is proved by the effectiveness of the system.

Remote patient monitoring: a comprehensive study

Abstract: Healthcare is a field that is rapidly developing in technology and services. A recent development in this area is remote monitoring of patients which has many advantages in a fast aging world population with increasing health complications. With relatively simple applications to monitor patients inside hospital rooms, the technology has developed to the extent that the patient can be allowed normal daily activities at home while still being monitored with the use of modern communication and sensor technologies. Sensors for monitoring essential vital signs such as electrocardiogram reading, heart rate, respiration rate, blood pressure, temperature, blood glucose levels and neural system activity are available today. Range of remote healthcare varies from monitoring chronically ill patients, elders, premature children to victims of accidents. These new technologies can monitor patients based on the illness or based on the situation. The technology varies from sensors attached to body to ambient sensors attached to the environment and new breakthroughs show contactless monitoring which requires only the patient to be present within a few meters from the sensor. Fall detection systems and applications to monitor chronical ill patients have already become familiar to many. This study provides a review of the recent advances in remote healthcare and monitoring in both with-contact and contactless methods. With the review, the authors discuss some issues available in most systems. The paper also includes some directions for future research.

Contact-Based Methods for Measuring Respiratory Rate

Abstract: There is an ever-growing demand for measuring respiratory variables during a variety of applications, including monitoring in clinical and occupational settings, and during sporting activities and exercise. Special attention is devoted to the monitoring of respiratory rate because it is a vital sign, which responds to a variety of stressors. There are different methods for measuring respiratory rate, which can be classed as contact-based or contactless. The present paper provides an overview of the currently available contact-based methods for measuring respiratory rate. For these methods, the sensing element (or part of the instrument containing it) is attached to the subject’s body. Methods based upon the recording of respiratory airflow, sounds, air temperature, air humidity, air components, chest wall movements, and modulation of the cardiac activity are presented. Working principles, metrological characteristics, and applications in the respiratory monitoring field are presented to explore potential development and applicability for each method.