Technical Feasibility of Respiratory Monitoring in Dogs Using Time-of-Flight Depth Imaging

Time-of-flight (ToF) depth imaging offers contactless observation of respiratory surface motion in veterinary patients. We investigated the technical feasibility of extracting canine respiratory waveforms and explored agreement between recorded camera-derived respiratory rates and concurrent manual counts. Depth images were acquired at a nominal 10 frames/s, and a fixed region of interest (ROI) supplied a mean depth signal. Clinical rates were obtained using Fourier spectral analysis with interpolation. Four dogs contributed eight sessions and 40 paired one-minute observations. Mean bias was +2.33 breaths/min (95% confidence interval −3.60 to +8.25), mean absolute error was 3.93 breaths/min, and exploratory repeated-measures limits of agreement were −10.40 to +15.05 breaths/min. One dog accounted for 69.4% of the absolute error and all observations above 25 breaths/min. Supplementary analyses compared spectral and peak-based estimates on identical inputs. An additional analysis of 27 ROI configurations in each of two recordings from one dog found maximum minute estimate changes of 7.50 and 7.80 breaths/min relative to a fixed baseline ROI. These findings demonstrate waveform extraction and dependence on spatial and temporal processing. They do not establish reliable respiratory rate measurement across dogs or respiratory rate ranges. The small independent sample, heterogeneous errors, incomplete original FFT configuration records and unquantified reference timing constrain the clinical comparison.