@conference {88, title = {A framework for secured collaboration in mHealth}, booktitle = {Collaboration Technologies and Systems (CTS), 2015 International Conference on}, year = {2015}, month = {06/2015}, abstract = {

We have designed a novel framework of services, protocols and technologies to ensure the secure collaboration in M2M networks, specifically in mobile health. The promise of mobile health to reform preventive self-care opens new doors for remote monitoring to improve health care communication. With cardiopulmonary resuscitation (CPR) as an example, we classify our M2M elements into services, roles, human-computer protocols and technologies through which we require trust, anonymity, scalability, and active detachment. We simulate a scenario in which a patient needs CPR and through the use of widely available technologies (such as a smartphone and secure web sockets) we demonstrate a technological collaboration that facilitates secure emergency mobile health services.

}, keywords = {cardiology, cardiopulmonary resuscitation, Cardiopulmonary resuscitation(CPR), Collaboration, Computers, CPR, health care, health care communication, human computer interaction, human-computer protocol, M2M network, machine to machine(M2M), Medical services, mHealth, Mobile communication, mobile computing, mobile health, Protocols, remote monitoring, Scalability, secure collaboration, secure emergency mobile health services, secured collaboration, security of data, servers, smart phones, smartphone}, doi = {10.1109/CTS.2015.7210450}, author = {Widick, Logan and Talkington, Josh and Bajwa, Garima and Ram Dantu} } @article {98, title = {Effective CPR Procedure With Real Time Evaluation and Feedback Using Smartphones}, journal = {IEEE Journal of Translational Engineering in Health and Medicine}, volume = {2}, year = {2014}, pages = {1-11}, abstract = {

Timely cardio pulmonary resuscitation (CPR) can mean the difference between life and death. A trained person may not be available at emergency sites to give CPR. Normally, a 9-1-1 operator gives verbal instructions over the phone to a person giving CPR. In this paper, we discuss the use of smartphones to assist in administering CPR more efficiently and accurately. The two important CPR parameters are the frequency and depth of compressions. In this paper, we used smartphones to calculate these factors and to give real-time guidance to improve CPR. In addition, we used an application to measure oxygen saturation in blood. If blood oxygen saturation falls below an acceptable threshold, the person giving CPR can be asked to do mouth-to-mouth breathing. The 9-1-1 operator receives this information real time and can further guide the person giving CPR. Our experiments show accuracy \>90\% for compression frequency, depth, and oxygen saturation.

}, keywords = {Acceleration, Accelerometers, blood, blood oxygen saturation, cardio pulmonary resuscitation, cardiology, compression depth, compression frequency, CPR, CPR parameters, CPR procedure, depth of compression, Feedback, Frequency measurement, frequency of compression, medical computing, mouth-to-mouth breathing, Oxygen, oxygen saturation, pneumodynamics, real-time evaluation, real-time systems, smart phones, smartphones, verbal instructions}, issn = {2168-2372}, doi = {10.1109/JTEHM.2014.2327612}, author = {Gupta, Neeraj and Dantu, Vishnu and Ram Dantu} } @conference {216, title = {Smart phone monitoring of second heart sound split}, booktitle = {2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society}, year = {2014}, month = {Aug}, abstract = {

Heart Auscultation (listening to heart sounds) is the basic element of cardiac diagnosis. The interpretation of these sounds is a difficult skill to acquire. In this work we have developed an application to detect, monitor, and analyze the split in second heart sound (S2) using a smart phone. The application records the heartbeat using a stethoscope connected to the smart phone. The audio signal is converted into the frequency domain using Fast Fourier Transform to detect the first and second heart sounds (S1 and S2). S2 is extracted and fed into the Discrete Wavelet Transform (DWT) and then to Continuous Wavelet Transform (CWT) to detect the Aortic (A2) and the Pulmonic (P2) components, which are used to calculate the split in S2. With our application, users can continuously monitor their second heart sound irrespective of ages and check for a split in their hearts with a low-cost, easily available equipment.

}, keywords = {acoustic signal processing, aortic component, biomedical equipment, Biomedical monitoring, cardiac diagnosis, cardiology, continuous wavelet transform, Continuous wavelet transforms, discrete wavelet transform, discrete wavelet transforms, fast Fourier transform, fast Fourier transforms, frequency domain, Heart, heart auscultation, heartbeat recording, medical signal processing, Monitoring, patient diagnosis, patient monitoring, pulmonic component, second heart sound split, smart phone monitoring, smart phones, stethoscope}, doi = {10.1109/EMBC.2014.6944050}, author = {Thiyagaraja, Shanti and Vempati, Jagannadh and Ram Dantu and Sarma, Tom and Dantu, Siva} }