People　easily　get　distracted　or　tired　after　long-duration　actions　such　as　driving　and　online　classes，which　can　lead　to　accidents　or　poor　efficiency.　To　detect　such　human　behaviors，a　head　motion　detection　method　based　on　low-resolution　infrared　array　sensors　is　proposed　with　the　protection　of　personal　privacy.　First，prominent　areas　of　the　human　body　are　extracted　based　on　image　processing　techniques.　Then　a　3D　image　fusion　algorithm　is　developed　to　extract　the　change　information　in　the　spatiotemporal　domain.　Finally，an　improved　residual　network　is　developed　to　achieve　head　motion　classification.　Ten　head　movements　are　designed　for　driving　and　online　classroom　scenarios.　Experimental　results　show　that　in　the　detection　range　of　50　cm　to　100　cm，our　average　recognition　rate　is　96.76%，and　the　processing　speed　is　9　frames　per　second，which　is　better　than　the　existing　state-of-the-art　algorithms.　The　accuracy　of　the　system　is　93.7%　when　it　is　applied　to　the　vehicle　experiment.　©　2023　Chinese　Optical　Society.　All　rights　reserved.