摘要
提出一种抽取微笑表情特征的近红外额耳穴信号小波分析方法,优点是无损间接测量脑额区的神经递质涨落。针对分别呈现平静或微笑表情的16名大学生被测者(男11人,女5人,平均年龄24±4岁),该方法选取右耳额穴,采集960nm近红外透射信号,做10级小波分解与重构,构造出超低频功率谱特征;统计结果表明,81%的受试者具有微笑小于平静的小波超低频功率谱特征。
A novel feature extraction method for smiling expression is proposed based on wavelet super-slow power spectrum of near infrared prefrontal cortex otopoint signal. The method merits in non-invasive indirect measurement of neurotransmitters fluctuation at subject's prefrontal cortex. Firstly, n = 16 subjects (5 females and 11 males) aged (24 ± 4) years old are selected showing separately in quiet or smiling expressions. And 960 nm near infrared transmissive signals at right-side prefrontal cortex otopoint are sampled in 1 000 Hz with total data length of 10 000- dot and filtered in band-pass of 0.1 Hz -40 Hz. Then, wavelet analysis with 10-stage decomposition and recon- struction is made for extracting the super-slow power spectrum feature of quiet versus smiling expression. Finally, the statistic result showed that 81% of subjects in smiling are with smaller feature values than in quiet expression.
出处
《电子器件》
CAS
2010年第1期113-116,共4页
Chinese Journal of Electron Devices
基金
国家自然科学基金资助(60572074)
江苏省高校自然科学研究项目资助(09KJB510017)
关键词
微笑表情
近红外光
额耳穴
小波分析
超低频功率谱
smiling expression
near infrared light
prefrontal cortex otopoint
wavelet analysis
super-slow power spectrum