PURPOSE: A depression diagnosis method is provided to check the status of mental health related to depression by measuring and analyzing an ECG(Electrocardiogram) signal and comparing an analyzed result with the result of a normal person. CONSTITUTION: A depression diagnosis method performs the following steps: a step of receiving an ECG signal(S200)； a step of converting the ECG signal into HRV(Heart Rate Variability)(S300)； a step of extracting frequency-domain characteristics and time-domain characteristics for the HRV(S400)； a step of inputting the characteristics into NEWFM(Neuro-Network with a Weighted Fuzzy Membership function) and making the NEWFM learn BSWFM(Bounded Sum of Weighted Fuzzy Membership functions)(S500)； and a step of easily diagnosing the status of depression by comparing with a predetermined value(S600). [Reference numerals] (S100) Step of providing affective contents stimulus including two or more modes to a user； (S200) Step of receiving an ECG signal during a preset time； (S300) Step of converting the received ECG signal into HRV； (S400) Step of extracting a frequency-domain characteristics and time-domain characteristics for the HRV； (S500) Step of inputting the extracted frequency-domain characteristics and time-domain characteristics into NEWFM and learning BSWFM of the weighted fuzzy membership function； (S600) Step of diagnosing the status of depression of the user by comparing the learned BSWFM of the weighted fuzzy membership function with a predetermined value본 발명은 우울증 진단을 위한 뉴로-퍼지 네트워크 기반의 데이터 분석 방법에 관한 것으로서, 보다 구체적으로는 (1) 미리 설정된 시간 동안, 심전도(Electrocardiogram, ECG) 신호를 수신하는 단계； (2) 상기 수신된 신호를 심박 변이도(Heart Rate Variability, HRV)로 변환하는 단계； (3) 상기 변환된 심박 변이도(HRV)에 대하여 주파수 영역 특징 및 시간 영역 특징을 추출하는 단계； 및 (4) 상기 추출된 주파수 영역 특징 및 시간 영역 특징을 각각, 가중 퍼지 소속 함수 기반의 퍼지 신경망(Neuro Network with a Weighted Fuzzy Membership function, NEWFM)에 입력하여, 가중 퍼지 소속 함수의 경계합(Bounded Sum of Weighted Fuzzy Membership functions, BSWFM)을 학습시키는 단계를 포함하는 것을 그 구성상의 특징으로
