PROBLEM TO BE SOLVED: To provide a sleep stage detection device, a sleep stage calculation device, and a sleep stage detection system, which reduce influences caused due to individual difference between subjects, and further precisely detect the sleep stage.SOLUTION: Brain wave data detected by three electrodes 11 to 13 are Fourier transformed to obtain spectral analysis data, calculation represented by X=δ/(δ+θ+α+β+emg) is executed based on δ, θ, α, and β waves included in the spectral analysis data and frontalis electromyogram (emg) to obtain the content rate X of the δ wave. The content rate X and first to third thresholds TH1, TH2, and TH3 are compared with each other, thereby determining which stage the subject is in, REM sleep stage, light non-REM sleep stage, or deep non-REM sleep stage. Since data of the frontalis electromyogram is used to obtain the content rate X, highly precise detection of the sleep stage is allowed to be detected reflecting the sleep stage of the subject.COPYRIGHT: (C)2013,JPO&INPIT【課題】被験者の個人差による影響を低減し、且つより高精度な睡眠状態を検出することが可能な睡眠状態検出装置、睡眠状態演算装置、及び睡眠状態検出システムを提供する。【解決手段】3個の電極11~13で検出される脳波データをフーリエ変換してスペクトル解析データを取得し、更に、該スペクトル解析データに含まれるδ波、θ波、α波、β波、及び前額筋電図(emg)に基づき、X=δ/(δ+θ+α+β+emg)の演算を実行してδ波の含有率Xを求める。そして、この含有率Xと第1~第3閾値TH1,TH2,TH3の比較により、被験者の睡眠状態がレム睡眠、浅いノンレム睡眠、及び深いノンレム睡眠のうちの何れであるかを検出する。そして、含有率Xを求める際に前額筋電図のデータを用いているので、より被験者の睡眠状態を反映した高精度な睡眠状態の検出が可能となる。【選択図】図1
