An Integrated Sensing Platform for Remote Fetus Continuous Monitoring

Technological developments on health sensing devices, associated with the growing computational capabilities of mobile devices, enable the creation of solutions that address mobility concerns of patients, especially those located on remote locations or facing mobility constraints. This paper proposes an integrated sensing platform, which works transparently with new sensing, portable equipment sensors, but maintaining as well compatibility with currently deployed commercial tools. This platform targets fetus health monitoring in pregnant women, presenting a new non-invasive portable alternative system that allows long-term pregnancy surveillance. Additionally, it can be applied to other users’ communities, such as remote elderly monitoring at home. We address technology adoption problems related to non-invasive, portable sensing technologies, data security and equipment heterogeneity.

[1]  Devra Lee Davis,et al.  Exposure Limits: The underestimation of absorbed cell phone radiation, especially in children , 2012, Electromagnetic biology and medicine.

[2]  J. Crowe,et al.  Compact long-term recorder for the transabdominal foetal and maternal electrocardiogram , 2006, Medical and Biological Engineering and Computing.

[3]  H. Jenkins Technical progress in fetal electrocardiography--a review. , 1986, Journal of perinatal medicine.

[4]  A. Kansal,et al.  Building a Sensor Network of Mobile Phones , 2007, 2007 6th International Symposium on Information Processing in Sensor Networks.

[5]  E. Mulder,et al.  Fetal electrocardiography: feasibility of long‐term fetal heart rate recordings , 2009, BJOG : an international journal of obstetrics and gynaecology.

[6]  F. Northington,et al.  A systematic review of the role of intrapartum hypoxia-ischemia in the causation of neonatal encephalopathy. , 2008, American journal of obstetrics and gynecology.

[7]  Z. Alfirevic,et al.  Continuous cardiotocography (CTG) as a form of electronic fetal monitoring (EFM) for fetal assessment during labour. , 2006, The Cochrane database of systematic reviews.

[8]  Leonidas J. Guibas,et al.  Mobiscopes for Human Spaces , 2007, IEEE Pervasive Computing.

[9]  Mark A. Hanson,et al.  Non-invasive fetal electrocardiography: Validation and interpretation , 2008 .

[10]  E. Mohammadi,et al.  Barriers and facilitators related to the implementation of a physiological track and trigger system: A systematic review of the qualitative evidence , 2017, International journal for quality in health care : journal of the International Society for Quality in Health Care.

[11]  Ralph Deters,et al.  Mobile-Based Medical Data Accessibility in mHealth , 2014, 2014 2nd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering.

[12]  Mirco Musolesi,et al.  Sensing meets mobile social networks: the design, implementation and evaluation of the CenceMe application , 2008, SenSys '08.

[13]  S. Thacker,et al.  Historical Controversy in Health Technology Assessment:: The Case of Electronic Fetal Monitoring , 2001, Obstetrical & gynecological survey.

[14]  J. Crowe,et al.  The feasibility of long-term fetal heart rate monitoring in the home environment using maternal abdominal electrodes. , 1995, Physiological measurement.

[15]  D I Fotiadis,et al.  A Non-invasive Methodology for Fetal Monitoring during Pregnancy , 2009, Methods of Information in Medicine.

[16]  G. Macones,et al.  Intrapartum Fetal Heart Rate Monitoring: Nomenclature, Interpretation, and General Management Principles , 2009 .

[17]  N. Fisk,et al.  Non‐invasive fetal electrocardiography in singleton and multiple pregnancies , 2003, BJOG : an international journal of obstetrics and gynaecology.

[18]  Bin Li,et al.  Extracting social and community intelligence from digital footprints , 2012, Journal of Ambient Intelligence and Humanized Computing.

[19]  Emiliano Miluzzo,et al.  A survey of mobile phone sensing , 2010, IEEE Communications Magazine.

[20]  L. Devoe,et al.  Electronic fetal monitoring: does it really lead to better outcomes? , 2011, American journal of obstetrics and gynecology.

[21]  Andrew Campbell,et al.  The Rise of People-Centric Sensing , 2008, IEEE Internet Computing.

[22]  José Luis Fernández Alemán,et al.  Assessing the privacy policies in mobile personal health records , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.