Ambulatory stress monitoring with a wearable bluetooth electrocardiographic device.

We tried to monitor stress by using a wearable one channel ECG device that can send ECG signals through Bluetooth wireless communication. Noxious physical and mental arithmetic stress was given three times repeatedly to healthy adults, and cortisol and catecholamines were measured serially from peripheral blood. At the same time, time domain and frequency domain parameters of heart rate variability (HRV) were calculated by taking precordial electrocardiogram. The intensity of correlation between subjective visual analogue scale (VAS) and catecholamine, cortisol, and HRV parameters according to stress was analyzed by using concordance correlation coefficients. The HRV triangular index and LF/HF ratio had high concordance correlation with the degree of stress in the physical stress model. In mental arithmetic stress model, the HRV triangular index and LF/HF ratio had weak concordance correlation with the degree of stress, and it had lower predictability than epinephrine. In both models, cortisol had some correlation with catecholamine, but it had little correlation with HRV parameters. HRV parameters using wearable one channel ECG device can be useful in predicting acute stress and also in many other areas.

A Study of Sofa-Type Capacitive Coupling Electrocardiograph System to Measure Stress Relief for Sleeping or Resting with Oxygen Taking.

Non-contact electrode type electrocardiograph system was researched in various fields, but few products are commercially available. In this study, we proposed a sofa-type capacitive coupling electrocardiograph which has possibilities to be commercialized. The base system is a commercially available oval shape sofa that provides oxygen. We developed a capacitive coupling electrocardiograph and embedded it into the base system. The system gives feedback by measuring the ECG signal on stress relief during resting with taking oxygen provided by the sofa. In the capacitive coupling electrocardiograph, it is inevitable to develop a suitable active electrode for the target system, so we developed that comprised of a surface electrode, electronics, and metal case. The surface electrode was made of PCB with two layers of copper plate: the top layer is for coupling function (coated with AU), and the bottom layer plays a role as a shield. The fabricated active electrode module is embedded into the sofa. The purpose of the developed electrocardiograph is to measure HRV of sofa users. The measured HRV was compared with that from a reference system by various coupling distances (cotton cloth thickness) to guarantee the quality of measured signals. The comparison result shows that RRI correlation was mostly over 0.99, SDNN variation rate was mostly under 1%, and LF/HF variation rate was less than 1% in the tested thicknesses.

Performance study of the wearable one-lead wireless electrocardiographic monitoring system.

This study attempts to compare and assess the performance of a wearable electrocardiogram (ECG) using a sensing fabric electrode and a Bluetooth network with a conventional ECG. A one-lead ECG examination was performed using Bioshirt and an iWorx 214 while walking or running at 3, 6, and 9 km per hour. A correlation coefficient of a heart rate variability (HRV) between these two devices was higher than 0.96 and power spectral density of HRV measured also showed an excellent agreement. Thus, both of these two ECG devices showed similar detection capability for R peaks. The measured values for wave duration and intervals of both devices concur with each other. The intensity of noise is controversial. The ECG device using a sensing fabric electrode and a wireless network showed an ECG signal detection and transmission capability similar to that of a conventional ECG device.

Deep learning-based classification with improved time resolution for physical activities of children.

BACKGROUND: The proportion of overweight and obese people has increased tremendously in a short period, culminating in a worldwide trend of obesity that is reaching epidemic proportions. Overweight and obesity are serious issues, especially with regard to children. This is because obese children have twice the risk of becoming obese as adults, as compared to non-obese children. Nowadays, many methods for maintaining a caloric balance exist; however, these methods are not applicable to children. In this study, a new approach for helping children monitor their activities using a convolutional neural network (CNN) is proposed, which is applicable for real-time scenarios requiring high accuracy. METHODS: A total of 136 participants (86 boys and 50 girls), aged between 8.5 years and 12.5 years (mean 10.5, standard deviation 1.1), took part in this study. The participants performed various movement while wearing custom-made three-axis accelerometer modules around their waists. The data acquired by the accelerometer module was preprocessed by dividing them into small sets (128 sample points for 2.8 s). Approximately 183,600 data samples were used by the developed CNN for learning to classify ten physical activities : slow walking, fast walking, slow running, fast running, walking up the stairs, walking down the stairs, jumping rope, standing up, sitting down, and remaining still. RESULTS: The developed CNN classified the ten activities with an overall accuracy of 81.2%. When similar activities were merged, leading to seven merged activities, the CNN classified activities with an overall accuracy of 91.1%. Activity merging also improved performance indicators, for the maximum case of 66.4% in recall, 48.5% in precision, and 57.4% in f1 score . The developed CNN classifier was compared to conventional machine learning algorithms such as the support vector machine, decision tree, and k-nearest neighbor algorithms, and the proposed CNN classifier performed the best: CNN (81.2%) > SVM (64.8%) > DT (63.9%) > kNN (55.4%) (for ten activities); CNN (91.1%) > SVM (74.4%) > DT (73.2%) > kNN (65.3%) (for the merged seven activities). DISCUSSION: The developed algorithm distinguished physical activities with improved time resolution using short-time acceleration signals from the physical activities performed by children. This study involved algorithm development, participant recruitment, IRB approval, custom-design of a data acquisition module, and data collection. The self-selected moving speeds for walking and running (slow and fast) and the structure of staircase degraded the performance of the algorithm. However, after similar activities were merged, the effects caused by the self-selection of speed were reduced. The experimental results show that the proposed algorithm performed better than conventional algorithms. Owing to its simplicity, the proposed algorithm could be applied to real-time applicaitons.

Sequential algorithm for the detection of the shockable rhythms in electrocardiogram.

We suggest a sequential algorithm for the detection of the ventricular fibrillation (VF) and ventricular tachycardia (VT) of a rate above 180 bpm, so called shockable rhythms. The built-in algorithm for ECG analysis embedded in the portable bio-signal sensing module is aimed to discriminate between shockable and non-shockable rhythms and its accuracy is analyzed. An algorithm for VF/VT detection is proposed to analyze every 1 s ECG episode using the past 8 s episodes. The method is tested with 844,587 ECG episodes from the widely accepted databases. A sensitivity of 86.8 % and a specificity of 99.4 % were obtained and compared with the previous results.

A preliminary study of the effect of electrode placement in order to define a suitable location for two electrodes and obtain sufficiently reliable ECG signals when monitoring with wireless system.

Most countries face high and increasing rates of cardiovascular disease. Each year, heart disease kills more Americans than cancer. Therefore, there has been a promising market for portable ECG equipment and it is increasing. To use portable ECG measuring devices, it is essential to define a suitable location for the measuring as we need to reduced electrode size and distance. This research proposes to study how the inter-electrode distance affects the signal and how the electrode pair should be placed on the chest in order to obtain a sufficiently reliable ECG signal to detect heart arrhythmias in any environment, such as home or work. Therefore, we developed a compact, portable patch type ambulatory ECG monitoring system, Heart Tracker, using a microprocessor for preliminary study of signal analysis. To optimize the electrode arrangement in wireless environment, we compared HT and standard 12 lead with changing electrode position.

Development of a patch type embedded cardiac function monitoring system using dual microprocessor for arrhythmia detection in heart disease patient.

A patch type embedded cardiac function monitoring system was developed to detect arrhythmias such as PVC (Premature Ventricular Contraction), pause, ventricular fibrillation, and tachy/bradycardia. The overall system is composed of a main module including a dual processor and a Bluetooth telecommunication module. The dual microprocessor strategy minimizes power consumption and size, and guarantees the resources of embedded software programs. The developed software was verified with standard DB, and showed good performance.

Development of an integrated obesity management waist belt system composed of calorie tracking and waist circumference measuring module for long term monitoring.

A waist belt type simple device was designed to monitor the individuals who are obese and want to maintain their consumed calories and waist circumference changes. Relatively long term monitoring with this device could help them maintain their health conditions. This devised system is composed of calorie tracking and waist circumference module. This study suggests feasible and meaningful results. If users' data are collected largely with this developed system, we can reveal the relationship between obesity and daily life pattern.

A basic study for patch type ambulatory 3-electrode ECG monitoring system for the analysis of acceleration signal and the limb leads and augmented unipolar limb leads signal.

A compact and portable device was designed for preliminary study of patch type ambulatory 3-electrode ECG monitoring system for limb leads and augmented unipolar limb leads signal analysis. The developed system also can measure and send the acceleration signals wirelessly during daily life to analyze the user's information. The 3-electrode system is feasible to provide the information of limb leads and augmented unipolar limb leads for further arrhythmia analysis and simultaneously shows lots of issues to be more broadly applicable and more powerful device.

A basic study for automatic waist circumference measurement using magnet with waist belt to assist obese management in daily life.

Waist circumference is a very important factor in deciding if someone has the potential for obesity, but there has been no device that automatically measures waist circumference. In this study, a new waist circumference measurable belt was devised and is accurate to 5mm resolution. The system is comprised of magnets and magneto-resistive sensors to measure waist circumference. A novel algorithm was developed to distinguish the belt moving direction. This belt system can assist in obesity and overweight management and a connection with IT and communication networks may make this system a more powerful tool.

A preliminary study for portable walking distance measurement system using ultrasonic sensors.

Efforts have been made to measure the distance traveled by humans in motion, in ways that are compact and accurate, for a long time. There are several ways to measure the distance moved by walking or running in daily life, some of which already use commercial products, but those methods are inaccurate. In this study, a new method is provided using ultrasonic sensors, and this is the fundamental study. The newly devised 'Portable Walking Distance Measurement System' was developed using ultrasonic wave characteristics and has approximately 90% accuracy. This result provides an opportunity to estimate human activities and the developed system would provide more comfort and an exact way to measure the walking distance in daily life and could be applied to exercise.

An Wearable Energy Expenditure Analysis System based on the 15-channel Whole-body Segment Acceleration Measurement.

The measurement of the amount of energy utilized during physical activity has generated considerable interests from various groups ranging from exercise physiologists to nutritionists and fitness center workers. To date, however, the existing energy expenditure estimation methods are not so reliable and compact. In this paper, we propose a new method for accurately and easily estimating energy expenditure during physical activity with a novel algorithm. This method involves acquiring acceleration signals through a 15-channel whole-body segment acceleration measurement system and then estimating the calories expended using a newly developed algorithm. The results of 3 subjects' experiments were compared with a commercially available mask type indirect calorimeter and a 9-axis accelerometry-based calorimeter. The results demonstrate that the proposed method provides a new and reliable way to estimate human energy expenditure during physical activity.