Wearable Heart Rate Sensor Systems for Wireless Canine Health Monitoring

Brugarolas, Rita; Latif, Tahmid; Dieffenderfer, James; Walker, Katherine; Yuschak, Sherrie; Sherman, Barbara L.; Roberts, David L.; Bozkurt, Alper

doi:10.1109/jsen.2015.2485210

Cited by 96 publications

(36 citation statements)

References 22 publications

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“…A number of research work addressed traditional ECG monitoring setups in various contexts such as hospitals [149][150][151], homes, or remote ambulatory settings [31,32,112,146,152]. Screening devices can be physically connected to processing devices [31,32,149,150], or wirelessly accessed [17,112,152,153]. Table 4.…”

Section: Traditional Ecg Monitoringmentioning

confidence: 99%

ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges

Serhani

Kassabi

Ismail

et al. 2020

Sensors

230

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Health monitoring and its related technologies is an attractive research area. The electrocardiogram (ECG) has always been a popular measurement scheme to assess and diagnose cardiovascular diseases (CVDs). The number of ECG monitoring systems in the literature is expanding exponentially. Hence, it is very hard for researchers and healthcare experts to choose, compare, and evaluate systems that serve their needs and fulfill the monitoring requirements. This accentuates the need for a verified reference guiding the design, classification, and analysis of ECG monitoring systems, serving both researchers and professionals in the field. In this paper, we propose a comprehensive, expert-verified taxonomy of ECG monitoring systems and conduct an extensive, systematic review of the literature. This provides evidence-based support for critically understanding ECG monitoring systems’ components, contexts, features, and challenges. Hence, a generic architectural model for ECG monitoring systems is proposed, an extensive analysis of ECG monitoring systems’ value chain is conducted, and a thorough review of the relevant literature, classified against the experts’ taxonomy, is presented, highlighting challenges and current trends. Finally, we identify key challenges and emphasize the importance of smart monitoring systems that leverage new technologies, including deep learning, artificial intelligence (AI), Big Data and Internet of Things (IoT), to provide efficient, cost-aware, and fully connected monitoring systems.

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Section: Traditional Ecg Monitoringmentioning

confidence: 99%

ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges

Serhani

Kassabi

Ismail

et al. 2020

Sensors

230

View full text Add to dashboard Cite

show abstract

“…Validation of this model in real-time is difficult. Vulture [28] ECG, PPG, Inertial Measurement Unit (IMU) Back…”

Section: Collarmentioning

confidence: 99%

The Design of an Automated System for the Analysis of the Activity and Emotional Patterns of Dogs with Wearable Sensors Using Machine Learning

et al. 2019

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The safety and welfare of companion animals such as dogs has become a large challenge in the last few years. To assess the well-being of a dog, it is very important for human beings to understand the activity pattern of the dog, and its emotional behavior. A wearable, sensor-based system is suitable for such ends, as it will be able to monitor the dogs in real-time. However, the question remains unanswered as to what kind of data should be used to detect the activity patterns and emotional patterns, as does another: what should be the location of the sensors for the collection of data and how should we automate the system? Yet these questions remain unanswered, because to date, there is no such system that can address the above-mentioned concerns. The main purpose of this study was (1) to develop a system that can detect the activities and emotions based on the accelerometer and gyroscope signals and (2) to automate the system with robust machine learning techniques for implementing it for real-time situations. Therefore, we propose a system which is based on the data collected from 10 dogs, including nine breeds of various sizes and ages, and both genders. We used machine learning classification techniques for automating the detection and evaluation process. The ground truth fetched for the evaluation process was carried out by taking video recording data in frame per second and the wearable sensors data were collected in parallel with the video recordings. Evaluation of the system was performed using an ANN (artificial neural network), random forest, SVM (support vector machine), KNN (k nearest neighbors), and a naïve Bayes classifier. The robustness of our system was evaluated by taking independent training and validation sets. We achieved an accuracy of 96.58% while detecting the activity and 92.87% while detecting emotional behavior, respectively. This system will help the owners of dogs to track their behavior and emotions in real-life situations for various breeds in different scenarios.

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“…HR of an animal is an indicator of its welfare, stress, distress, emotions and excitements. The method for measuring the heart rate is known as photoplethysmography (PPG) [15]. The Pulse Sensor shown in Fig.5 is a plug and play device integrated with the amplification and noise cancellation circuit that makes the measurement simple and fast.…”

Section: Fig 4 Temperature Sensor -Ds18b0mentioning

confidence: 99%

Iot Based Physical Condition Screening System for Animals

2019

ijrte

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Animal husbandry and its health monitoring is one of the prime facts for the socio-economic development of a nation. This necessitates monitoring the wellbeing of the animals and thereby increasing the food supply of the country. Advancement in wearable biosensors and wireless communication technologies help in ubiquitous E-health monitoring of animals. The proposed system is build up of recent technologies to screen the physical condition of the animals continuously from anywhere and at anytime. The vital parameters like body temperature, heart rate and position tracking are acquired using respective sensors. The collected data are transmitted wirelessly over internet and are stored in a database using IoT technology. The system also alerts the farmers/care takers at the critical conditions. The records that reflect the physical condition of animals collected in the database helps veterinary doctors to provide effective treatment

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Wearable Heart Rate Sensor Systems for Wireless Canine Health Monitoring

Cited by 96 publications

References 22 publications

ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges

ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges

The Design of an Automated System for the Analysis of the Activity and Emotional Patterns of Dogs with Wearable Sensors Using Machine Learning

Iot Based Physical Condition Screening System for Animals

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