# A Review of Methods and Applications for a Heart Rate Variability Analysis
## 7 Applications of HRV Analysis
### Psychiatric Disorder Detection  
The dynamic regulation of the heart can be significantly affected by psychological emotions and activities [162; 163]. Hence, people with psychiatric problems are at risk of developing cardiovascular diseases [164]. Multiple symptoms of mental disorders are also associated with the disruption of ANS. For instance, depressed people frequently have dry mouth, constipation/diarrhea, and sleeplessness. In the last few decades, many researchers have examined the feasibility of an HRV analysis to elucidate the physiology of psychiatric diseases and their relation to the cardiovascular system [165]. A study by [PERSON] et al. (2001) found that patients with depression and cardiovascular conditions have lower short- and long-term HRV feature values [166]. Other usual mental ailments, such as anxiety disorders, frequently coexist with ANS disorders because of their close relationship. An analysis of HRV data was used in a work by [PERSON] et al. (2009) to understand the relationship between anxiety and malfunction in the ANS [167]. It has been shown that several antipsychotic medications can harm the functioning of the ANS. In particular, ANS dysfunction and abnormal cardiac repolarizations are detected in people medicated with the antipsychotic drug clozapine [168]. These findings point to the possibility that both the schizophrenia disease and the medication prescribed for its therapy could add to the increased likelihood of coronary sickness. Patients who are untreated for their schizophrenia exhibit a reduction in HRV feature values like RMSSD, pNN50, and high-frequency spectral power compared to healthy controls, suggesting a decreased vagal modulation [168]. Some more papers on the application of an HRV analysis in psychiatric disorders are discussed in Table 5. \begin{table}
\begin{tabular}{c c c c c} \hline
**Author,** & **Feature Extraction** & **Feature Selection/Reduction** & **Classifiers** & **Inference** \\
**Year** & **Methods Used** & **Methods Employed** & **Used** & **Inference** \\ \hline \multirow{4}{*}{[PERSON] et al. (2021) [159]} & \multirow{4}{*}{Time-domain and frequency-domain methods} & One-way ANOVA, or the Wilcoxon rank-sum test for continuous variables, and the chi-square test or exact probability test for the categorical variables & \multirow{4}{*}{-} & This study examined the link between plasma PTH fragments and HRV in CKD5 patients. It was found that neither (1–84) PTH nor (7–84) PTH affected HRV features. \\ \cline{1-1} \cline{4-4} [PERSON] et al. (2021) [160] & Time-domain and frequency-domain methods & \(T\)-test or Mann–Whitney test, and chi-square or Fisher’s exact test & \multirow{4}{*}{-} & The values of the HRV features were reduced in end-stage renal disease (ESRD) patients in comparison with healthy volunteers. It also showed that hemoglobin and serum albumin correlated positively with HRV features. \\ \hline [PERSON] et al. (2021) [161] & Time-domain and frequency-domain methods & Pearson coefficient correlation analysis and multiple linear regression analysis & \multirow{4}{*}{-} & The study discovered a correlation between elevated plasma growth differentiation factor 15 (GDF15) plasma levels and lower HRV. \\ \hline \end{tabular}
\end{table} 
Table 4: List of published papers in recent years that have used novel HRV analysis methods for the detection of renal failure.