Enhanced Brady-Tachy Heart Automotive (BT-Heartomotive) Device for Heart Rate Monitoring during Driving

Driving with brady-tachy syndrome is one of the main causes of car accidents. In order to prevent drivers from brady-tachy driving, there is a strong demand for driver monitoring systems. Other than problems in driving attitudes and skills, road accidents are also caused by uncontrollable factors such as medical conditions and drowsiness. These factors can be avoided by having early detection. Therefore, the brady-tachy heart automotive so-called BT-Heartomotive device is developed. This BT-Heartomotive device can detect early signs of drowsiness and health problems by measuring the heart rate of the drivers during driving. The device also could use the data to send an alert to the passengers that they’re in precaution. The device shows a good accuracy in the detection of the heart rate level. The device comprised three main components; wristband, monitor and integrated mobile applications. Heart rate measurement can reveal a lot about the physical conditions of an individual. The BT-Heartomotive device is simple, easy to use and automated.

Optimal Design of Interval Type-2 Fuzzy Heart Rate Level Classification Systems Using the Bird Swarm Algorithm

In this paper, the optimal designs of type-1 and interval type-2 fuzzy systems for the classification of the heart rate level are presented. The contribution of this work is a proposed approach for achieving the optimal design of interval type-2 fuzzy systems for the classification of the heart rate in patients. The fuzzy rule base was designed based on the knowledge of experts. Optimization of the membership functions of the fuzzy systems is done in order to improve the classification rate and provide a more accurate diagnosis, and for this goal the Bird Swarm Algorithm was used. Two different type-1 fuzzy systems are designed and optimized, the first one with trapezoidal membership functions and the second with Gaussian membership functions. Once the best type-1 fuzzy systems have been obtained, these are considered as a basis for designing the interval type-2 fuzzy systems, where the footprint of uncertainty was optimized to find the optimal representation of uncertainty. After performing different tests with patients and comparing the classification rate of each fuzzy system, it is concluded that fuzzy systems with Gaussian membership functions provide a better classification than those designed with trapezoidal membership functions. Additionally, tests were performed with the Crow Search Algorithm to carry out a performance comparison, with Bird Swarm Algorithm being the one with the best results.

Heart rate and hurtful behavior from teens to adults: Paths to adult health

A low resting heart rate across development from infancy to young adulthood relates to greater aggression/hostility. Adult aggression and a high heart rate relate to health risk. Do some aggressive individuals retain low heart rate and less health risk across development while others show high heart rate and more risk? A longitudinal sample of 203 men assessed as teens (age 16.1) and adults (mean age 32.0) permitted us to assess (a) stability of heart rate levels and reactivity, (b) stability of aggression/hostility, and (c) whether change or stability related to health risk. Adults were assessed with Buss–Perry measures of aggression/hostility; teens with the Zuckerman aggression/hostility measure. Mean resting heart rate, heart rate reactivity to speech preparation, and aggression/hostility were moderately stable across development. Within age periods, mean heart rate level, but not reactivity, was negatively related to hostility/aggression. Maintaining low heart rate into adulthood was related to better health among aggressive individuals relative to those with increasing heart rate into adulthood. Analyses controlled for weight gain, socioeconomic status, race, health habits, and medication. Low heart rate as a characteristic of hostile/aggressive individuals may continue to relate to better health indices in adulthood, despite possible reversal of this relationship with aging.

Sliding Mode Control for Heart Rate Regulation of Electric Bicycle Riders

In this paper a new controller for electric bicycles is proposed to maintain a desired heart rate level and improve the riding experience of cyclists. The controller achieves this by adequately adjusting the motor assistance without affecting the cycling velocity. First, a human heart rate model is fitted to experimental data to model the heart rate response of cyclists during different exercises. Then, a sliding mode controller is designed to keep the human heart rate at a predefined level. Furthermore, a feedforward controller is introduced into the system to improve both the tracking performance and riding experience. The feedforward controller consists of an inverse human heart rate response model, which estimates the necessary rider torque for a desired heart rate level. The controller is implemented with a commercial electric bicycle. Simulation and experimental results are presented to assess the validity of the controller. Whereas the sliding mode controller itself achieves good tracking performance, the sliding mode control combined with the feedforward control additionally reduces the maximal exerted rider torque and improves the riding experience.

Autonomic Stress Response Modes and Ambulatory Heart Rate Level and Variability

The major goals of this study were (1) to determine consistency of autonomic response modes to different laboratory stressors, and (2) to evaluate the strength of the association between autonomic response modes and ambulatory heart rate and variability. The sample consisted of 45 healthy participants. Parasympathetic (PNS) and sympathetic (SNS) reactivity to and recovery from laboratory stressors (handgrip, logical-mathematical, mirror-tracing, and rumination tasks) were estimated by high frequency heart rate variability (HF-HRV), preejection period (PEP), and baroreflex sensitivity (BRS). Ambulatory HR was measured for 24 h on a work and a nonwork day, counterbalanced. As BRS was less reliable compared to PEP and HF-HRV, the latter two parameters were selected for the computation of SNS/PNS patterns. Autonomic modes were consistent across tasks and more stable during the recovery periods. Moreover, recovery appeared to be sensitive to the emotionality of tasks. Reactivity and recovery patterns differed as a function of gender, with women showing higher vagal tone at baseline, higher HR reactivity to the logical task, greater BRS decrease during the rumination task, and a larger decrease in vagal tone during recovery after the rumination task. After controlling for gender and baseline HR and variability, autonomic profiles during reactivity and recovery periods captured substantially different ambulatory information. Specifically, autonomic profiles during reactivity significantly predicted ambulatory HR level during waking hours, whereas autonomic profile during recovery was linked with ambulatory HRV. Coactivation of SNS and PNS activity was associated with the highest ambulatory HR levels and variability. Findings from the laboratory were consistent with a dimensional autonomic model viewing SNS and PNS contributions to heart rate on orthogonal axes and individual stress response stereotypy. Laboratory task-related autonomic reactivity and recovery may reflect parallel differences in HR level and variability in everyday life.