This is the first study investigating OSAS patients’ snoring using the snoring energy spectrum. The findings suggest that there are at least four different energy types of the snoring sounds (snore map types) that are fairly associated with the severity of OSAS. The fine reliabilities of snore map measuring indicate that snore map typing represents a simple trustworthy way to classify the energy pattern of each OSAS patient’s snoring in nature sleep. Notably, snore map type cannot be differentiated by current subjective snoring questionnaires. These different distributions of snoring map may reflect the multiple vibrating sites of the upper airway, including contributions from the velum, tongue base, pharyngeal wall, and epiglottis.
Perez-Padilla and coworkers firstly described that most of the power of snoring noise was below 2,000 Hz, and patients with OSAS had residual energy at 1,000 Hz, whereas the nonapneic snorers did not 
. They also recommended that the ratio of power above 800 Hz to power below 800 Hz of the first post-apneic snore could be used to separate simple snorers from patients with OSAS. In our study, we used a relatively long distance (100 cm) to measure the full-night snoring sounds. Not only the first post-apneic snore but also the remaining snores following apneic events were all analyzed. We found that snoring signs between 800 Hz and 850 Hz frequently continued to snoring signals below 800 Hz. Therefore, we categorized snores with the frequency domain from 850 Hz to 2000 Hz to “high-frequency snores”. The snore map type 3–4, containing full-night high-frequency snore energy, was associated with higher AHI and these results further supported Perez-Padilla’s findings.
Beck et al. found that there are two distinctly different patterns of snoring sound waveform by using power spectrum as follows: complex-waveform snore and simple-waveform snore. They found that brief airway closure induce collide of the airway walls and produce complex-waveform snores, whereas simple-waveform snores result from oscillation of a patent airway lumen 
. Solà-Soler et al. used linear prediction autoregressive modeling with a low order for spectral envelope estimation of a piezoelectric contact sensor placed beside the cricothyorid notch 
. They found the spectral envelope concentrated in a reduced number of formant distributions in simple snorers and indicated that the mechanism of snore production has some common characteristics. By contrast, the standard deviation of some snoring formant frequencies is significantly higher in OSAS patients than in simple snorers. As Fiz’s 
and Ben-Israel’s 
findings, the snore signals also became instable with various amplitudes and durations in apneic phase. However, most of the OSAS patients had various durations of snoring and different proportions of simple- and complex-waveform snores.
In our study, we tried to simplify the formant distribution, pitch density, and running variance of snoring sounds by snoring energy spectrum typing. For this purpose, we developed a semi-automatic graphical user interface to automatically detect full-night snoring energy and to manually decide which type of snore map is based on audio and visual perception. Snore map type 1 () is composed of primary simple-waveform snore powers (), and snore map type 4 () consists of principle complex-waveform snoring powers of a 6-hour sleep (). This finding suggested that type 1 subjects seems to represent hypopneic predominate OSAS and type 4 patients may depict predominant apneic OSAS. Moreover, our observations suggested that a higher grade of snore map typing symbolizes a more complex sound energy form and a severer degree of OSAS. The presence of B3-energy is associated with a higher chance of transient airway closures with multiple generators of snoring and with the increasing AHI. Of note, our proposed method did not consider the time interval between snores that has been regarded as an important predicator of severe OSAS 
. Nevertheless, the clinicians can easily and quickly decide which snoring patient is priority for standard PSG examination based on the snore map type.
Miyazaki et al. found that the lower frequency snoring sound (fundamental frequency [ff]
102.8±34.9 Hz) is characteristic of the soft palate obstruction and the higher frequency snoring sound (ff
331.7±144.8 Hz) resulting from the tonsil/tongue base obstruction according to the intraluminal pressure of the upper airway 
. Agrawal et al. used sleep endoscopy to examine the site of vibration and sound frequency spectrum, and found that the tonsillar and palatal vibrations produce similar low-frequency snoring sound spectra (Fpeak
170 Hz & 137 Hz, respectively) and tongue-base vibrations result in high-frequency snoring (Fpeak
1,243 Hz) 
. The mid-frequency snoring sound is the feature of epiglottic snores (ff
249.4±79.7 Hz 
490 Hz 
). To our knowledge, OSAS patients often have different durations and multiple generators of snoring. Therefore, we defined a type 2 snore map consists of low- and mid-frequency snores and a type 3 snore map was composed of low- and high-frequency snores. Accordingly, we supposed that a higher grade of snore map typing may be resulted from a multi-site vibration in male OSAS patients. In our preclusive results, patients with snore map type 2 resembled patients with snore map type 1 in demographic and polysomnographic parameters () although their snoring acoustic parameters differed to some extent (). The differences in clinical factors between the snore map type 3 and the snore map type 4 were insignificant despite some different acoustic parameters. Nevertheless, this classification system is aimed to illustrate the therapeutic targets of anti-snoring treatment.
Currently, there is no standard method for snoring acquisition. Therefore, some of those previous studies used ambient microphones placed at a specific location, some others used contact microphones or sensors usually placed at the trachea. In addition, the sampling frequencies and filtering bands were usually different. Accordingly, caution must be taken when comparing our results with the results of those other studies. Aside from those outlined above, this preliminary study has other limitations. Although this study enrolled patients with four different energy types of their snoring sounds, this snore map typing method should be further validated in the patients with primary snoring, and in the peer norms. Besides, the effect of nasal obstruction, a crucial factor of snoring 
, needs a further survey. The random error related to one-night studies should be further evaluated since this kind of snoring surveys are not reliable 
. Moreover, the snore map measured the energy between 40 Hz and 2,000 Hz in mid-aged male OSAS patients. Higher frequency region of the snore sounds (>5,000 Hz) has been reported recently to be associated with OSAS snorers 
. Accordingly, larger and more detail investigations will be useful to consider other important OSAS-related factors including age, gender, ethnicity, and high frequency snores. In addition, a prospective study is warranted to access the change of snore map types after anti-snoring treatment or OSAS therapy.
In conclusion, there are plenty of publications that have addressed the spectral analysis of snores, in subjects with and without OSAS. This study further supported the importance of analysis of the full-night snoring sounds. The highest intensity of the special-band snores (40 Hz–2,000 Hz or 851 Hz–2,000 Hz) and the mean frequency of total-frequency and high-frequency snoring sounds are reliable snoring sound parameters to predict the AHI among male OSAS patients; however, these predicators could not be measured by current subjective questionnaires appropriately. Snore map types can be classified easily and reliably, and are fairly related to the severity of OSAS. The clinical values of snore map typing such as differentiation of primary snoring and OSAS in larger populations and changes after OSAS treatment needs a further investigation.