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Ignite/Hackanooga2012: Difference between revisions
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→Team Idea 7: Long-Term Medical Monitoring & Crisis Event Handling System
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<p>Team Idea 7: Long-Term Medical Monitoring & Crisis Event Handling System === | |||
WHO: Amr Ali & Dmitri Boulanov <br /><br /> | WHO: Amr Ali & Dmitri Boulanov <br /><br /> | ||
WHAT: A cloud-based complex event processing and monitoring system using existing equipment for signal input will create value for both the patients and their providers.<br/> | WHAT: A cloud-based complex event processing and monitoring system using existing equipment for signal input will create value for both the patients and their providers.<br /> | ||
</p><p>During the hackathon, we propose to work on a simple app prototype, which will aggregate signal information from multiple existing devices. A simple event based alert could also be implemented. We plan to implement a fall-detection system, which may be utilized by the elderly population, using the sensors and open APIs (Android) available at our disposal. Upon a detected fall, the user will be able to choose to notify an emergency service or an emergency contact. More literature on fall simulation and detection may be found here: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0037062 | |||
During the hackathon, we propose to work on a simple app prototype, which will aggregate signal information from multiple existing devices. A simple event based alert could also be implemented. | <br /> | ||
<br/> | </p><p>With the emergence of biomedical signal monitoring devices, many people identify the importance of self-monitoring in keeping with good health. To stay fit, runners use mobile device applications to keep track of their heart rate and speed, which they can analyze after completing their exercise. Advances in modern biomedical signal monitoring will allow for deeper and more informative description of one’s health state at any given moment.<br /> | ||
</p><p>Existing technologies like pulse oximeters, glucose meters, EKG and ECG sensors presently allow for the monitoring of the elderly and patients with chronic diseases as well as general lifestyle tracking (Bachmann et al, 2012). Zeo and Fitbit are examples of commercially available monitoring equipment that has been adopted by the public in recent years. However, there is no backend infrastructure that goes along with this type of hardware. Due to the current limitations of live analysis and the lack of signal interpretation, these tools provide only nonessential functions. For example, a patient would need a trained physician to analyze an EKG signature.<br /> | |||
With the emergence of biomedical signal monitoring devices, many people identify the importance of self-monitoring in keeping with good health. To stay fit, runners use mobile device applications to keep track of their heart rate and speed, which they can analyze after completing their exercise. Advances in modern biomedical signal monitoring will allow for deeper and more informative description of one’s health state at any given moment.<br/> | </p><p>NEEDS: A FitBit device ($100 at http://www.fitbit.com/product/specs) {other options are Wahoo Fitness BlueHR, Scosche myTrek, iBG Star}, a Neurosky Mindwave Mobile EEG device ($130 at http://store.neurosky.com/products/mindwave-mobile), more C++/Java server-side developers (people with experiencing implementing a back-end to handle app requests), Android/iOS developers, physician contacts, UX/UI folk, quantitative physiologists <br /><br /> | ||
</p> | |||
Existing technologies like pulse oximeters, glucose meters, EKG and ECG sensors presently allow for the monitoring of the elderly and patients with chronic diseases as well as general lifestyle tracking (Bachmann et al, 2012). Zeo and Fitbit are examples of commercially available monitoring equipment that has been adopted by the public in recent years. However, there is no backend infrastructure that goes along with this type of hardware. Due to the current limitations of live analysis and the lack of signal interpretation, these tools provide only nonessential functions. For example, a patient would need a trained physician to analyze an EKG signature.<br/> | |||
NEEDS: A FitBit device ($100 at http://www.fitbit.com/product/specs) {other options are Wahoo Fitness BlueHR, Scosche myTrek, iBG Star}, a Neurosky Mindwave Mobile EEG device ($130 at http://store.neurosky.com/products/mindwave-mobile), more C++/Java server-side developers (people with experiencing implementing a back-end to handle app requests), Android/iOS developers, physician contacts, UX/UI folk, quantitative physiologists <br /><br /> | |||
===Team Idea 8: City Budget/Priorities Impact Visualizer === | ===Team Idea 8: City Budget/Priorities Impact Visualizer === | ||