Autonomic Nervous System Assessment Based on HRV Analysis During Virtual Reality Serious Games

2021 ◽  
pp. 756-768
Author(s):  
Mariana Jacob Rodrigues ◽  
Octavian Postolache ◽  
Francisco Cercas
2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
R Fenici ◽  
M Picerni ◽  
D Brisinda

Abstract Background Quantitative assessment of individual body adaptability to physical training performed with the purposes of health maintenance is particularly necessary in the elderly age, to avoid the risk of overstrain induced by inappropriate exercises workload and physical stress. For that purpose, heart rate monitors and heart rate variability (HRV) analysis are nowadays commercially available. However, their reliability to guide individualized fitness training in elderly people needs to be tested, knowing that users might not have medical education. Objective To preliminary quantify autonomic nervous system (ANS) responses to graded physical effort and recovery in healthy elderly basing on the parasympathetic nervous system (PNSi), the sympathetic nervous system (SNSi) and the stress (STRi) indices, derived by short-term and time-varying HRV analysis. Methods ECG of a 75 healthy male subject was monitored, from April to November 2020, during three times/week training sessions with a professional bike–ergometer. Each session consisted of 10 minutes baseline rest, 5 minutes warm-up, 30 minutes work and 10 minutes recovery. According to age, the training workload was graded from low (65–75 watt/min), to moderate (75–85 watt/min), semi-intensive (85–95 watt/min) and intensive (95–110 watt/min). For this pilot study, ECG data of only 40 training sessions (10 sessions for each workload to evaluate reproducibility) were analyzed with Kubios Premium software (version 3.4.1), in the time (TD) and frequency (FD) domains, with nonlinear (NL) methods and with time-varying (TV) algorithms. Short-time HRV was calculated from 2-minutes intervals. The PNSi, SNSi and STRi induced by each workload were averaged and compared. Results Average values of PNSi, SNSi and STRi were significantly different (p<0.05) among training sessions carried out with different workloads (Table 1A) and among measurements obtained at rest, at every 5 minutes step of each 30 minutes training session, and at 1 and 5 minutes of recovery (Table 1B). Interestingly, the correlation between SNSi and STRi was strictly linear (R= 0,98), whereas that between PNSi and STRi was better fitted by a cubic function (R=0,82 with cubic vs 0.68 with linear function), when evaluated either as a function of the sessions' workloads (Figure 1A), or of four time-intervals of each training session (Figure 1B). PNSi and SNSi were inversely correlated, with cross-point at about 15 minutes of training and 75 watt/min workload. Conclusions The calculation of PNSi, SNSi and STRi from HRV analysis is an efficient method for quick and simplified quantitative assessment of dynamic ASN adaptation to effort-induced stress from HRV analysis. If confirmed, the method may be useful for safer and even remote monitoring of training/rehabilitation in elderly. However, more detailed evaluation of spectral and NL parameters may be necessary to interpret more complex patterns of abnormal cases. FUNDunding Acknowledgement Type of funding sources: None. Table 1 Figure 1


Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6549
Author(s):  
Chun-Ju Hou ◽  
Yen-Ting Chen ◽  
Mycel Capilayan ◽  
Yu-Sian Lin ◽  
Min-Wei Huang ◽  
...  

As the proportion of elderly people continues to grow, so does the concern about age-related cognitive decline. Serious games have been developed for cognitive training or treatment, but measuring the activity of the autonomic nervous system (ANS) has not been taken to account. However, cognitive functioning has been known to be heavily influenced by the autonomic nervous system (ANS), and ANS activity can be quantified using heart rate variability (HRV). This paper aims to analyze the physiological response in normal elderly people as they play two types of serious games using HRV features from electrocardiography (ECG). A wearable device designed in-house was used to measure ECG, and the data from this device was pre-processed using digital signal processing techniques. Ten HRV features were extracted, including time-domain, nonlinear, and frequency-domain features. The experiment proceeds as follows: rest for three minutes, play a cognitive aptitude game, rest for another three minutes, followed by two reaction time games. Data from thirty older adults (age: 65.9 ± 7.34; male: 15, female: 15) were analyzed. The statistical results show that there was a significant difference in the HRV between the two types of games. From this, it can be concluded that the type of game has a significant effect on the ANS response. This can be further used in designing games for the elderly, either for training or mood management.


2014 ◽  
Vol 117 (2) ◽  
pp. 267-276 ◽  
Author(s):  
I. Corazza ◽  
G. Barletta ◽  
P. Guaraldi ◽  
A. Cecere ◽  
G. Calandra-Buonaura ◽  
...  

Author(s):  
Gitika Yadu ◽  
Suraj Kumar Nayak ◽  
Debasisha Panigrahi ◽  
Sirsendu Sekhar Ray ◽  
Kunal Pal

This chapter investigates the effect of a motivational song (stimulus) on the physiology of the autonomic nervous system and the electrical activity of the heart. Five min electrocardiogram (ECG) signals were acquired from 19 volunteers during the resting and the post-stimulus conditions. The RR intervals (RRIs) were extracted. Recurrence analysis of the RRI time series indicated a higher alteration (acceleration or deceleration) in the heart rate along with the reduction of the causality and patterned behavior of the RRIs. The exact alteration in the ANS physiology was examined using heart rate variability (HRV) analysis. The results of the HRV analysis suggested an increase in the parasympathetic activity in the post-stimulus condition. The alteration in the cardiac activity was analyzed using time domain and joint time-frequency domain analyses of ECG signals. The results suggested an alteration in the cardiac electrical activity of the heart in the post-stimulus condition.


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