Feasibility of Remote Camera-Based Respiratory Motion Detection in Hospitalized Dogs Using the InsectEye Image-Analysis Application: A Pilot Study

Noncontact camera-based detection of respiratory motion may support low-burden surveillance of hospitalized dogs, particularly at night. This pilot study evaluated the feasibility of the InsectEye image-analysis application for detecting visually identifiable respiratory motion in selected infrared nighttime video segments. An initial parameter optimization was performed using 13 one-minute video segments from nine dogs. The selected analysis conditions were subsequently evaluated in Experiment 1 using five 5 min video recordings from four dogs. Experiment 2 further assessed respiratory rate estimation using the same validation dataset. InsectEye-detected events were compared with visually confirmed respiratory motion using time-synchronized review. Two criteria were assessed: Both-only, requiring detection of both inspiratory- and expiratory-related motion, and Both+Either, accepting detection of either or both phases. Detection performance improved when the threshold was reduced from 10 to 8, particularly with the 256 × 120 mesh. The 256-120_15_8 condition yielded the highest mean detection rate (87.93 ± 1.87%), fewer false-negative events, and shorter continuous non-detection duration, although false-positive detections increased. The Both+Either criterion performed better than the Both-only criterion. These findings support the feasibility of camera-based respiratory motion detection under selected favorable conditions, but larger studies using physiological respiratory reference methods are required before clinical monitoring or alerting applications can be established.