2020
DOI: 10.1007/978-3-030-49666-1_17
|View full text |Cite
|
Sign up to set email alerts
|

Methods for Assessing the Subject’s Multidimensional Psychophysiological State in Terms of Proper Rehabilitation

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1

Citation Types

0
3
0

Year Published

2020
2020
2021
2021

Publication Types

Select...
2

Relationship

2
0

Authors

Journals

citations
Cited by 2 publications
(3 citation statements)
references
References 5 publications
0
3
0
Order By: Relevance
“…The HR signal was determined from the BVP by the algorithm proposed by the Empatica wristband designers. The analysis method was the same for both BVP and HR and involved short-term signal fragments and the determination of statistical and entropy-based features [ 80 , 81 ]. Due to the characteristics of the HR signal, it was not filtered before further calculations.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…The HR signal was determined from the BVP by the algorithm proposed by the Empatica wristband designers. The analysis method was the same for both BVP and HR and involved short-term signal fragments and the determination of statistical and entropy-based features [ 80 , 81 ]. Due to the characteristics of the HR signal, it was not filtered before further calculations.…”
Section: Discussionmentioning
confidence: 99%
“…Based on the available literature [ 9 , 10 , 34 , 35 , 81 ], for each part of the EDA, the same statistical parameters as for the heart signals were computed. Furthermore, the following coefficients were also computed from the EDA signal: total energy, mean and median energy of the signal, entropy, coefficient of the slope of the regression line allowing to determine the trend—tonicity of signal, coefficients of regression line shift, a distance of values of consecutive EDA samples from the regression line, number of signal intersections with the regression line and the quadratic metric of the discrepancy between predicted and observed data (obj).…”
Section: Discussionmentioning
confidence: 99%
“…The components of the D4S system include a TOF (Time-of-Flight) camera for the detection of selected anthropometric points and calculation of basic spinal curvatures, two thermal imaging cameras for monitoring temperature changes on the back and face, a device for measuring the distribution of foot pressure on the ground and for measuring the moment of the forces that rotate the lower limb called Rotenso (the platform with red components in Figure 1b). Monitoring of the patient's physiological functions is possible using the Empatica E4 wristband, which records heart rate variability signals, body temperature and electrodermal activity, allowing for a comprehensive assessment of the patient's health status before, during and after rehabilitation [40,41]. Furthermore, the cage is equipped with an original system for attaching the belt on the pelvis (orange-red clamp, Figure 1b) allowing for constant monitoring of its angular position in the sagittal, frontal and horizontal planes, which both controls and supports the optimal positioning of the pelvis, whereas during the therapy, it gradually reduces this movement, thus increasing lumbar and clavicular stability.…”
Section: Setupmentioning
confidence: 99%