Challenge
0

Slack Channel Guardian Angel

Summary

As an ALS patient or a family member, I want to make sure that caregivers are alerted in case of critical events. On other hand, I also would welcome a more proactive continuous support to reduce the daily burden of the condition. An automated connection with medical professionals records would help.

Description

 ALS people require caregiver support which can be both punctual and time-critical (breathing support, falls) as well as chronic (pain, speech). On the other hand one also needs  to keep the patients on track, for example taking the right medication at the right time. There are caregivers in the picture, but the patient may need help when the caregiver is not around. This can cause additional stress, especially as the patient may be temporarily unable to alert the caregiver or the patient may simply be unaware they should be alerting the caregiver.There are already existing solutions (e.g. respiration alarms , other passive monitoring systems), but they are not integrated and do cause a number of false alarms.The challenge is to bring all these data points together, as unobtrusive as possible which can actively support the patient daily, and also help caregivers remotely support the patient. This may for instance integrate different data flows from wearable sensors, reminders for adherence for medication, but also alert systems interfacing. The events recorded and displayed in such a way that they can be shared easily with the doctors and caregivers .Key themes of attention: respiration, mobility, speech.

Thematic Area

4 -Measuring Causal Factors

Patient Champion

Champion R.L. (6)

Team Composition would benefit from

Web , mobile app development; UX / interface expert,  ALS care expert;  ML , speech analysis specialist.

References/Resources

https://en.wikipedia.org/wiki/Amyotrophic_lateral_sclerosis

Wish list / call for resources

Sensor data streams (real or synthetic);  

08.11.2020 12:00

Hackathon finished

23.10.2020 16:17

Team forming

GuillaumeAzarias has joined!

23.10.2020 12:00

Hackathon started

22.10.2020 22:13 ~ giovanni_nisato

Synchronized

Readme fetched from source

22.10.2020 12:02 ~ giovanni_nisato

Worked on documentation

22.10.2020 11:44 ~ giovanni_nisato

Synchronized

Readme fetched from source

22.10.2020 11:44 ~ giovanni_nisato

Worked on documentation

22.10.2020 09:37 ~ oleg

Synchronized

Readme fetched from source

22.10.2020 09:37

Project started

Initialized by oleg 🎉

4. Measurement of causal factors

Today you may feel fine, but tomorrow you may feel it is the worst day of your life. What changed? Is it something you did or is it something that happened to you? These are questions that patients ask themselves all the time. What external and internal factors influence my well-being? These factors may not always be obvious, such as, for example, the weather. Patients would like to be able to measure these influences automatically and match them to their subjective well-being. This could provide them with deeper insight into their situation while also providing an unbiased (e.g. without flaws of memory) overview of the course of their disease, which could support them in meetings with HCPs.

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