@article{foster_brugarolas_walker_mealin_cleghern_yuschak_clark_adin_russenberger_gruen_et al._2020, title={Preliminary Evaluation of a Wearable Sensor System for Heart Rate Assessment in Guide Dog Puppies}, volume={20}, ISSN={["1558-1748"]}, url={https://doi.org/10.1109/JSEN.2020.2986159}, DOI={10.1109/JSEN.2020.2986159}, abstractNote={This paper details the development of a novel wireless heart rate sensing system for puppies in training as guide dogs. The system includes a harness with on-board electrocardiography (ECG) front-end circuit, inertial measurement unit and a micro-computer with wireless capability where the major research focus of this paper was on the ergonomic design and evaluation of the system on puppies. The first phase of our evaluation was performed on a Labrador Retriever between 12 to 26 weeks in age as a pilot study. The longitudinal weekly data collected revealed the expected trend of a decreasing average heart rate and increased heart rate variability as the age increased. In the second phase, we improved the system ergonomics for a larger scale deployment in a guide dog school (Guiding Eyes for the Blind (Guiding Eyes)) on seventy 7.5-week-old puppies (heart rate coverage average of 86.7%). The acquired ECG based heart rate data was used to predict the performance of puppies in Guiding Eyes’s temperament test. We used the data as an input to a machine learning model which predicted two Behavior Checklist (BCL) scores as determined by expert Guiding Eyes puppy evaluators with an accuracy above 90%.}, number={16}, journal={IEEE SENSORS JOURNAL}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Foster, Marc and Brugarolas, Rita and Walker, Katherine and Mealin, Sean and Cleghern, Zach and Yuschak, Sherrie and Clark, Julia Condit and Adin, Darcy and Russenberger, Jane and Gruen, Margaret and et al.}, year={2020}, pages={9449–9459} }
 @article{majikes_brugarolas_winters_yuschak_mealin_walker_yang_sherman_bozkurt_roberts_2017, title={Balancing noise sensitivity, response latency, and posture accuracy for a computer-assisted canine posture training system}, volume={98}, ISSN={["1095-9300"]}, DOI={10.1016/j.ijhcs.2016.04.010}, abstractNote={This paper describes a canine posture detection system composed of wearable sensors and instrumented devices that detect the postures sit, stand, and eat. The system consists of a customized harness outfitted with wearable Inertial Measurement Units (IMUs) and a base station for processing IMU data to classify canine postures. Research in operant conditioning, the science of behavior change, indicates that successful animal training requires consistent and accurate feedback on behavior. Properly designed computer systems excel at timeliness and accuracy, which are two characteristics most amateur trainers struggle with and professionals strive for. Therefore, in addition to the system being ergonomically designed to ensure the dog׳s comfort and well-being, it is engineered to provide posture detection with timing and accuracy on par with a professional trainer. We contend that providing a system with these characteristics will one day aid dogs in learning from humans by overcoming poor or ineffective timing during training. We present the initial steps in the development and validation of a computer-assisted training system designed to work outside of laboratory environments. The main contributions of this work are (a) to explore the trade-off between low-latency responses to changes in time-series IMU data representative of posture changes while maintaining accuracy and timing similar to a professional trainer, and (b) to provide a model for future ACI technologies by documenting the user-centered approach we followed to create a computer-assisted training system that met the criteria identified in (a). Accordingly, in addition to describing our system, we present the results of three experiments to characterize the performance of the system at capturing sit postures of dogs and providing timely reinforcement. These trade-offs are illustrated through the comparison of two algorithms. The first is Random Forest classification and the second is an algorithm which uses a Variance-based Threshold for classification of postures. Results indicate that with proper parameter tuning, our system can successfully capture and reinforce postures to provide computer-assisted training of dogs.}, journal={INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES}, author={Majikes, John and Brugarolas, Rita and Winters, Michael and Yuschak, Sherrie and Mealin, Sean and Walker, Katherine and Yang, Pu and Sherman, Barbara and Bozkurt, Alper and Roberts, David L.}, year={2017}, month={Feb}, pages={179–195} }
 @inproceedings{majikes_mealin_rita_walker_yuschak_sherman_bozkurt_roberts_2016, title={Smart connected canines: IoT design considerations for the lab, home, and mission-critical environments (invited paper)}, DOI={10.1109/sarnof.2016.7846739}, abstractNote={The canine-human relationship continues to grow as dogs become an increasingly critical part of our society. As reliance on dogs has increased from simple companionship, to service dogs, urban security, and national defense, the opportunities for enhanced communications between the working canine and their handler increase. Wireless sensor networks and the Internet of Things (IoT) can extend traditional canine-human communication to integrate canines into the cyber-enabled world. This is what we call the Smart Connected Canine (SCC). Canine-computer interaction is sufficiently different from human-computer interaction so as to present some challenging research and design problems. There are physical and performance limits to what a dog will naturally tolerate. There are communications requirements for monitoring dogs, monitoring the environment, and for canine-human communications. Depending on the working environment there are different performance, security, and ergonomic considerations. This paper summarizes three example canine-human systems we presented earlier along with their Ion data characteristics and design criteria in order to explore how smart connected canines can improve our lives, the future of smart connected canines, and the requirements on IoT technologies to facilitate this future.}, booktitle={2016 ieee 37th sarnoff symposium}, author={Majikes, J. J. and Mealin, S. and Rita, B. and Walker, K. and Yuschak, S. and Sherman, B. and Bozkurt, A. and Roberts, D. L.}, year={2016}, pages={118–123} }
 @inproceedings{gonzales_walker_keller_beckman_goodell_wright_rhone_emery_gupta_2015, title={Textile sensor system for electrocardiogram monitoring}, DOI={10.1109/vcacs.2015.7439568}, abstractNote={Wearable self-powered medical devices have long been a goal of the medical community. The ability to constantly monitor the patient's vital signs for abnormalities, in addition to alerting first responders to immediate problems, would allow for more rapid medical treatment. As the population of the United States ages, low-cost and ubiquitous medical devices will improve the ability of medical personnel to diagnose potential health issues early, thus increasing the survival rate and decreasing the potential complications. Electrocardiograms are a major focus of the medical community due to the prevalence of heart issues among elderly Americans, and as the cost of sensors and wireless communication decreases, new devices are possible. This paper describes a Bluetooth-based, dry electrode electrocardiogram monitoring system seamlessly integrated into a T-shirt. The shirt used three dry silver-based electrodes to collect the ECG signal and streamed the resulting signal to an Android smartphone for analysis.}, booktitle={2015 Virtual Conference on Application of Commercial Sensors}, author={Gonzales, L. and Walker, K. and Keller, K. and Beckman, D. and Goodell, H. and Wright, G. and Rhone, C. and Emery, A. and Gupta, Rachana}, year={2015} }