Measuring Vital Signs Using Smart Phones

Smart phones today have become increasingly popular with the general public for its diverse abilities like navigation, social networking, and multimedia facilities to name a few. These phones are equipped with high end processors, high resolution cameras, built-in sensors like accelerometer, orientation-sensor, light-sensor, and much more. According to comScore survey, 25.3% of US adults use smart phones in their daily lives. Motivated by the capability of smart phones and their extensive usage, I focused on utilizing them for bio-medical applications. In this thesis, I present a new application for a smart phone to quantify the vital signs such as heart rate, respiratory rate and blood pressure with the help of its built-in sensors. Using the camera and a microphone, I have shown how the blood pressure and heart rate can be determined for a subject. People sometimes encounter minor situations like fainting or fatal accidents like car crash at unexpected times and places. It would be useful to have a device which can measure all vital signs in such an event. The second part of this thesis demonstrates a new mode of communication for next generation 9-1-1 calls. In this new architecture, the call-taker will be able to control the multimedia elements in the phone from a remote location. This would help the call-taker or first responder to have a better control over the situation. Transmission of the vital signs measured using the smart phone can be a life saver in critical situations. In today's voice oriented 9-1-1 calls, the dispatcher first collects critical information (e.g., location, call-back number) from caller, and assesses the situation. Meanwhile, the dispatchers constantly face a "60-second dilemma"; i.e., within 60 seconds, they need to make a complicated but important decision, whether to dispatch and, if so, what to dispatch. The dispatchers often feel that they lack sufficient information to make a confident dispatch decision. This remote-media-control described in this system will be able to facilitate information acquisition and decision-making in emergency situations within the 60-second response window in 9-1-1 calls using new multimedia technologies.

[1]  J. Cohn,et al.  Noninvasive pulse wave analysis for the early detection of vascular disease. , 1995, Hypertension.

[2]  K. Tremper,et al.  Pulse oximetry. , 1989, Anesthesiology.

[3]  J. L. Walle,et al.  Medicine & Science in sports & Exercise , 2010 .

[4]  George Demiris,et al.  A comparison of communication models of traditional and video-mediated health care delivery , 2005, Int. J. Medical Informatics.

[5]  K. Shelley Photoplethysmography: Beyond the Calculation of Arterial Oxygen Saturation and Heart Rate , 2007, Anesthesia and analgesia.

[6]  Kang B. Lee,et al.  Standard for a Precision Clock Synchronization Protocol for Networked Measurement and Control Systems , 2004 .

[7]  C. Lim,et al.  Evaluation of blood pressure changes using vascular transit time , 2006, Physiological measurement.

[8]  D. Cavouras,et al.  A Simple algorithm to monitor HR for real time treatment applications , 2009, 2009 9th International Conference on Information Technology and Applications in Biomedicine.

[9]  A. Mitchell,et al.  Left ventricular ejection time: a potential determinant of pulse wave velocity in young, healthy males , 2003, Journal of hypertension.

[10]  James S Hagood,et al.  Estimation of airway obstruction using oximeter plethysmograph waveform data , 2005, Respiratory research.

[11]  P. Szilagyi,et al.  Bate's guide to physical examination and history taking , 1995 .

[12]  Cullen Jennings,et al.  Relay Extensions for the Message Sessions Relay Protocol (MSRP) , 2007, RFC.

[13]  V. L. Clark,et al.  Clinical Methods: The History, Physical, and Laboratory Examinations , 1990 .

[14]  J. N. Watson,et al.  Standard pulse oximeters can be used to monitor respiratory rate , 2003, Emergency medicine journal : EMJ.

[15]  Gerard P. Rabalais Telemedicine and the Pediatric Tertiary Care Center , 2009 .

[16]  Ronald L Gellish,et al.  Longitudinal modeling of the relationship between age and maximal heart rate. , 2007, Medicine and science in sports and exercise.

[17]  Mark Handley,et al.  SIP: Session Initiation Protocol , 1999, RFC.

[18]  Yves Lepage,et al.  MBONE, multicasting tomorrow's Internet , 1996 .

[19]  G. Mensah,et al.  Stroke volume/pulse pressure ratio and cardiovascular risk in arterial hypertension. , 1999, Hypertension.

[20]  J. Alfie,et al.  Contribution of stroke volume to the change in pulse pressure pattern with age. , 1999, Hypertension.

[21]  Kiyoshi Yasuda,et al.  Networked reminiscence therapy for individuals with dementia by using photo and video sharing , 2006, Assets '06.

[22]  Daniel Dickerson,et al.  Integrating Point-to-Point Videoconferencing Into Professional Development of Rural Elementary School Science Teachers , 2006 .

[23]  M. Angela Sasse,et al.  Sharp or smooth?: comparing the effects of quantization vs. frame rate for streamed video , 2004, CHI '04.

[24]  J A Dunbar,et al.  A virtual clinic: telemetric assessment and monitoring for rural and remote areas. , 2004, Rural and remote health.

[25]  Lynn Clemow,et al.  Anxiety and outcome expectations predict the white-coat effect , 2005, Blood pressure monitoring.

[26]  H Kenneth Walker,et al.  Clinical methods: The history, physical, and laboratory examinations , 1976 .

[27]  William M. K. Trochim,et al.  Research methods knowledge base , 2001 .

[28]  Christian Huitema,et al.  Session Initiation Protocol (SIP) Extension for Instant Messaging , 2002, RFC.

[29]  George Demiris,et al.  An Evaluation Framework for a Rural Home-Based Telerehabilitation Network , 2005, Journal of Medical Systems.

[30]  W. T. Ritchie,et al.  Clinical Methods , 1902, Edinburgh Medical Journal.

[31]  Gabriella Convertino,et al.  A new UPnP architecture for distributed video voice over IP , 2006, MUM '06.