Closed anirudh4792 closed 6 years ago
binarybottle
commented
6 years ago Case 1: the measure is movement and the dimension is frequency (or pattern?).
Case 2: if possible, it would be good to include what the app is actually measuring.
Case 3: again, measure is movement with frequency (or pattern?) dimension.
shnizzedy
commented
6 years ago Each of these cases is where inferencing can shine.
For case 2, I'd argue that the example is a sign, although not necessarily a very precise one. An app would have a pretty big job if it tried to measure verbal and non-verbal responses and distinguished those from other verbal and non-verbal behaviors any time the user's name is called or the user is spoken to directly. I can see how some types of response could be subjective, but I suspect most responses to being called by name or spoken to directly are observable and measurable.
Can I proceed to start mapping them?
I'd say yes, map where you can! (This is probably a new sheet though, right?)
shnizzedy
commented
6 years ago Replaced by %5 📋 Convert Spreadsheets to RDF
Linking our 3 major spreadsheets (disorders, neutral states, projects/tech) together
LHS - App/Wearable, Sensors, Measures, ‘Things’ that app/wearable CLAIMS to address RHS - Signs/Symptoms in turn linked to neutral states and disorders
Case 1: Quantifiable measure to sign no6 (measure): Frequency of tremors TO no716 (sign): Tremors developing during, or shortly after, hallucinogen use
Case 2: App CLAIMS to address symptom directly no65 (app): A Smartphone Application to Measure Response to Name in Everyday Environments TO no109 (symptom): Failure to respond when name called or when spoken directly to
Case 3: App CLAIMS to monitor (‘things’ ⇒ symptoms) VIA (measure ⇒ sign) no5 (app): Spire claims to monitor no2 (thing) stress by analysing no4 (measure): Rate of respiration no2 (thing) stress linked to multiple symptoms no240: Difficulty controlling worry, no900: feeling keyed up or tense, no214: Persistent and excessive worry about experiencing an untoward event (e.g., getting lost, being kidnapped, having an accident, becoming ill) that causes separation from a major attachment figure.
Simple readable examples: piezoelectric sensors measure chew patterns in the jaw which in turn can be used to monitor how much you eat/drink device measures speech which could be used to monitor mania/depression as claim: Mania is typically marked by speech that's loud and rapid, often with erratic leaps from topic to topic. Longer pauses or breaks can indicate depression
Can I proceed to start mapping them? Very excited with the implications and results we could infer from this, and the questions we could raise/answer Eg App ‘xyz’ uses measure ‘abc’ measured by sensor ‘def’ to reduce (claim) symptom ‘ghi’ How much of the symptom space is claimed to be measured by technologies? If a PPG is used to monitor symptom ‘ghi’ and my device has a PPG, can my device be used to monitor symptom ‘ghi’ as well? etc..