The　traditional　cockpit　display-control　system　usually　has　great　many　instruments　and　much　complex　information,　which　leads　to　the　pilots　to　take　a　long　time　to　be　familiar　with　the　cockpit　interface　and　often　cause　accidents　when　emergencies　happen.　Thus　it　is　necessary　to　evaluate　the　cognitive　workload　of　the　pilots　under　multitask　conditions.　A　simplified　evaluation　method　of　cognitive　workload　by　approximate　entropy　(ApEn)　of　electroencephalography　(EEG)　is　proposed　in　this　paper.　We　design　a　series　of　experiments　about　the　flight　instruments,　which　have　different　instrument　number,　pointer　speed,　and　operation　difficulty,　and　collect　the　EEG,　interval　time　(IT),　and　misjudgment　rate　(MR),　then　classify　and　analyze　these　data　with　ApEn　algorithm,　traceability,　and　dualistic　linear　regression　method.　It　can　be　found　that　ApEn　is　increased　with　increasing　experiment　difficulty,　which　shows　that　ApEn　can　be　used　as　the　evaluation　criteria　of　cognitive　workload.　As　the　ApEn　and　the　number　of　dipoles　have　a　positive　correlation　relationship,　the　cognitive　workload　and　ApEn　are　both　changed　with　increasing　the　number　of　brain　dipoles.　Taking　MR　and　IT　as　the　independent　variables,　and　ApEn　as　the　dependent　variable,　we　obtain　an　empirical　formula　to　simplify　the　assessment　process　of　the　cognitive　workload.　This　study　concludes　that　ApEn　can　be　used　as　the　evaluation　criteria　of　cognitive　workload,　which　could　be　applied　in　the　ergonomics　estimation　of　human-interface　interaction　field.