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    <subfield code="b">Otieno, Francis Odhiambo</subfield>
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    <subfield code="a">Otieno, Francis Odhiambo.</subfield>
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    <subfield code="a">A mobile based health-monitoring system for patients with diabetes /</subfield>
    <subfield code="c">by Francis Odhiambo Otieno.</subfield>
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    <subfield code="c">c2014.</subfield>
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    <subfield code="a">xx leaves : </subfield>
    <subfield code="b">ill. ; </subfield>
    <subfield code="c">29 cm.</subfield>
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    <subfield code="a">Thesis ()--Oregon State University, .</subfield>
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    <subfield code="a">Diabetes is a chronic disease that needs to be regularly monitored to keep the blood sugar level within normal ranges. This monitoring depends on a diabetic treatment plan that is periodically reviewed by the doctor. Currently, patients have to do the medical checkups and examinations from prescribed appointments after every periodic Doctor visit. According to the result of this medical checkups and examination, the doctor may need to modify the treatment plan. This creates a major problem since this process is tiring and time consuming while it creates a challenge of untimely monitoring due to lack of consistency and accuracy records of glucose levels making diabetes management unmanageable and a threat to the patient&amp;apos;s life. Mobile computing can improve the quality of the patients&amp;apos; life by providing systems that help diabetes patients to monitor and control their diseases. These applications can help the doctors by providing remote monitoring to the patient. A mobile-based monitoring solution can be combined with communication technologies to present an integrated diabetesmonitoring tool. In this work we propose, a smartphone based monitoring and analysis application that automatically gathers inference for diabetes monitoring parameters such as blood glucose and weight, diet and exercise done by patient, in a manner that is transparent to the patient. This work includes an inference, which provides notifications while remotely monitoring patient health condition at the convenience of the patient and health practitioners. Generation of inference rules was done with the aid of two medical doctors. The work was tested and the results analyzed showed that it was able to gather inference and monitor patient conditions while giving alerts and notifications. All of the components yielded accurate analyses of glucose levels of the patients and it proved to be a novel utility in helping in monitoring of Diabetic cases. The patients reported satisfaction with the system because they felt connected to their physician and also giving them reminders for checking their sugar level, taking insulin or notification in case of critical levels.</subfield>
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    <subfield code="a">Also available on the World Wide Web.</subfield>
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    <subfield code="a">Includes bibliographical references (leaves - ).</subfield>
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    <subfield code="a">Diabetes.</subfield>
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    <subfield code="a">Mobile computing.</subfield>
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    <subfield code="u">http://hdl.handle.net/11071/4326</subfield>
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