# A Review of Methods and Applications for a Heart Rate Variability Analysis
## 7 Applications of HRV Analysis
### Sleep Apnea Detection  
Sleep is important for the proper functioning of the human body [109]. The brain passes through various stages of sleep as a person sleeps. They are mainly classified as rapid eye movement (REM) and non-rapid eye movement (NREM) [110]. Both of these phases are continually repeated during sleep [109]. When a person does not have typical cycles of REM and non-REM sleep, the body may face a variety of negative impacts, including weariness, a decrease in capacity to focus, disruptions in body metabolism, and other similar symptoms, even stroke [111]. Sleep apnea is one of the many diseases that disrupt these healthy sleeping cycles. It is a sleeping ailment categorized by recurrent starting and stopping of breathing while sleeping. Sleep apnea patients experience muscles at the back of their throats getting stretched and becoming more constricted, thus disrupting the normal breathing process [112]. This is a highly prevalent condition often observed more frequently in males than in women. Patients of any age can be affected by this ailment. However, middle-aged individuals are more likely to have it [113]. Sleep apnea can be treated if the patient is aware of the symptoms of sleep apnea, which reduces risk factors, and discusses future treatment options with their doctor [114]. Snoring and occasional breathing disruptions during sleep are the common symptoms of this disorder. Other indications include an abrupt awakening accompanied by shortness of breath, a headache upon waking, insomnia, focus issues, irritability, and hypersomnia. Sleep apnea has been related to various significant health problems such as diabetes, stroke, hypertension, obesity [115], and high blood pressure. Although this cannot be cured, it can be treated with various methods such as behavioral therapy, positive pressure therapy, oral breathing equipment, and even surgery [116; 117]. Several pieces of research have been executed in the arena of sleep apnea diagnoses since an early diagnosis of the disease can reduce patient mortality. An HRV analysis has found several applications in the field of sleep, including assessing the severity of sleep apnea, categorizing sleep stages, and detecting sleep apnea events [118; 119]. The consequence of disruptive sleep apnea (OSA) severity on HRV features was examined by [PERSON] et al. (2021) [120]. The research was conducted on 1247 persons, among which 426 were healthy and 821 had OSA. The time-domain and non-linear HRV features exhibited less complexity and increased sympathetic dominance in OSA patients. Thus, the authors proposed an HRV analysis as a potential marker of cardiovascular activity in such patients. Recently, [PERSON] et al. (2022) studied the relationship between the apnea-hypopnea index (AHI) and HRV in OSA patients. The authors analyzed the 24 h Holter monitoring-based HRV data and polysomnography data of 62 OSA patients. The results suggested that day/night VLF and LF ratios decreased with the increased severity of OSA. These features were also observed to associate independently with the AHI. Table 2 shows some HRV analysis research conducted for sleep apnea detection.