The following is an abstract concerning the above topoc. It passed and the students mentioned had a chance to present it in Nairobi, at the 2nd Africa International Biotechnology and Biomedical Conference whose theme was Africa’s Road to Dignity Beyond the Millenium Development Goals through Biotechnology and Biochemical Research.

Evaluation of m- Health sensing programs in adressing the plight of HIV in Africa.

Marcia Apiyo OBONDI, Kevin Tony Okoth*

School of Medicine, Maseno University, Kisumu, Kenya.


Mobile communication offers an effective means of bringing healthcare services to developing-country citizens. Recent studies by United Nations reveal that approximately 64% of all mobile phone users can now be found in the developing world. This growing ubiquity of mobile phones is a central element in the promise of mobile technologies for health. In Kenya today, stringent policies need to be established to address the low turnover of patients requiring HIV care. m-Health, due to its large user base can be an effective way for creating an interactive experience between HIV-infected patients and healthcare workers thereby improving patient care. In light of that, this study intends to assess role of m-Health in health education and support of HIV-infected patients in Kenya. The intended way of doing this is by integrating Bluetooth enabled devices in healthcare to improve HIV management and care thereby ensuring active patient participation in self-care.


Physiological conditions sensors implanted in the patients.

Mobile phone connected to the physiological sensor.

A relay system that receives data from the mobile phone.

An external communication unit that communicates data to a remote medical monitoring station i.e. to the hospital via cellphone network or internet.


A randomized three-month study of HIV-infected patients aged between 18-40 years, seeking care at Jaramogi Oginga Odinga Teaching and Referral Hospital in Western Kenya was done. A total of 200 participants were randomly assigned to the intervention (n=100) or to standard care (n=100). Participants and health workers were taken through a six-week training period. A BCC (body coupled communication) device was implanted onto 100 of participants to monitor CD4 cell count/leukocyte count. Primary data obtained from the test and control groups were analyzed using SPSS. Mean was used for descriptive statistics and correlation and linear regression used for assessing the relationship between BCC and participants’ status.

Results: The experimental group (patients with the BCC implants) showed significant improvement in their health status due to their active participation in self-care by timely response to the BCC signals. On the other hand, the control group (patients without the implants) showed minimal improvement in health status due to the reluctance in making regular visits to the hospital. The physiological sensor used near field capacitance body coupled protocol to detect the levels of CD4 cell, emerging opportunistic infections and vital signs. The results were automatically registered and sent a text on the patient’s mobile phone. In an emergency situation where the CD4 count fell below 100 cells/cm3, severe alternation in vital signs and when the opportunistic infections overwhelmed the body. An alarm was relayed via mobile phone to the hospital and the nurse in charge received notifications on the same, called the patients and provided the necessary care.


from the study, the BCC alarm repeatedly went off on detection of slight physiological imbalance in the patient and this went on sequentially until the patient sent a notification of visit to the hospital. In cases of failure of response within 12 hours, the nurse in charge contacted the patients who then booked an appointment and visited the hospital.


The m-Health program significantly reduced unexpected use of hospital/clinic services and resulted in fewer medical appointments. Though BCC looks promising, extensive experimentation is required; more measurements need to be done on different subjects with different body structures. We propose that integration of m-Health into healthcare has a positive significant impact on patients’ wellbeing.


[1] J. Bae, K. Song et al “A 0.24-nj/b wireless body-area-network transceiver with scalable double-fsk modulation,” Solid-State Circuits, IEEE Journal of, vol. 47, no.1, pp. 310-322, jan. 2012.

[2] Lo, B., Thiemjarus, S., King, et al.2005, Body Sensor Networks – A Platform for Pervasive Healthcare Monitoring. In International Conference on Pervasive Computing.

[3] Shnayder, V., et al. 2005. Sensor Networks for Medical Care. In Havard University Technical Report TR-08-05.

[4] Guang-Zhong Yang, Body Sensor Networks, Springer-Verlag New York, Inc, Secaucus, NJ, 2006

[5] Yoo, H.J. et al. 2006. Experimental Evaluation of Body Channel for BSN. In International Workshop on Wearable and Implantable Body Sensor Networks, pp.15-20

[6] Nawal, Ravi,Kaushal Vaidaya et al, 2012. Lives through mobile health assessing the global market opportunity.GSMA. (February 2012)


Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s