A movement analysis application for the Mobile Health Platform
|1 September 2014|
|31 December 2016|
|More info (PDF):|
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With the global penetration of smart phones and communication networks, millions of people now use mobile devices as a daily tool for communication, data transfer and much more. As a consequence, possibilities have opened up for new technological advancements to emerge. These technological advancements involve the creation of external hardware solutions that reap the benefits of smart-phones' capabilities in order to become more cost effective and mobile. Devices which enable remote monitoring of patients have been identified as one of the areas most uniquely suited to grow in tandem with this technology. On an international setting, this specific field of technology is often referred to as mHealth and is predicted to grow substantially in the upcoming years.
Given the projections for demographic change and the increased demand for health care resources in the future, there is a need to transition our health care system from one where patients passively receive instructions from the doctor, to one where patients are active in managing their own treatment in a partnership with doctors. This new health care paradigm is often referred to as person-centered care or patient-centric care. In order to speed up and facilitate this process we must empower patients with technologies to support self-assessment and self-management.
Self-management is what persons suffering from chronic diseases do to manage their own illness on a daily basis. It is the ability of the patient to deal with symptoms, treatment, and lifestyle changes. One important part of the process is to actively monitor symptoms and manage their impact on quality of life. Unfortunately, for many of these patients there is a lack of continuous and objective assessment of their symptoms and how they change over time. An assessment of the severity of a patient's condition is usually done at the clinic, very few times a year. In between these session, however, the patient can only rely on his or hers subjective feeling of how their symptoms interfere with their normal daily activities.
One problem which arises is that small, progressive changes in symptom severity are usually not felt by the patient. Another problem is that a person's assessment of their own symptoms is very subjective and can be influenced by mood or other psycho-social factors. Not being able to perceive or quantify how symptoms change can also impact patients' motivation to comply with treatment. In some cases, it may even complicate or delay adjusting the patient's medication dosage.
Current mobile monitoring technologies combined with decision support systems can considerably facilitate self-management for patients by: 1) providing objective assessment of symptoms and other health-related information; 2) modeling how symptoms affect and are affected by daily activities and other health factors; and 3) supporting decision by predicting the impact of certain actions or treatment.