Wearable Technology for Detecting Significant Moments in Individuals with Dementia

Table 4

Creating customized algorithms for dementia participants from ANS signals.

ANS signal	Feature extracted	Thresholds	Scaling factor
(A) Dyad 1 dementia participant Mary
Electrodermal activity	First derivative of signal over 10 s sliding window, incremented in 0.5 s intervals	Positive EDA change of 0.24 µs	5
Heart rate	Local maxima and minima	Peak prominence of 20 bpm	0.05
Skin temperature	First derivative of signal over 15 s sliding window, incremented in 0.5 s intervals	Positive or negative temperature change of 0.05°C	1
(B) Dyad 2 dementia participant Elisa
Electrodermal activity	First derivative of signal over 20 s sliding window, incremented in 0.5 s intervals	Positive EDA change of 0.25 µs	4
Heart rate	Local maxima and minima	Peak prominence of 25 bpm	0.96
Skin temperature	First derivative of signal over 15 s sliding window, incremented in 0.5 s intervals	Positive or negative temperature change of 0.11°C	8.4
(C) Dyad 3 dementia participant Irene
Electrodermal activity	First derivative of signal over 10 s sliding window, incremented in 0.5 s intervals	Positive EDA change of 0.25 µs	4
Heart rate	Local maxima and minima	Peak prominence of 35 bpm	0.06
Skin temperature	First derivative of signal over 25 s sliding window, incremented in 0.5 s intervals	Positive or negative temperature change of 0.02°C	9