Pulse Detection from Head Motions in Video

Technology

The cyclical movement of blood from the heart to the head via the abdominal aorta and the carotid arteries causes the head to move in a periodic motion. The Inventors’ algorithm detects pulse from this movement. This method takes an input video of a person’s head and returns a pulse rate as well as a series of beat locations which can be used for the analysis of beat-to-beat variability. The motion of the head is extracted using feature tracking, upon which the motion corresponding to the pulse is isolated and projected onto a 1D signal to extract individual beat boundaries from the peaks of the trajectory. For this, principal component analysis (PCA) is used and the component whose temporal power spectrum best matches a pulse is selected.The algorithm projects the trajectories of feature points onto this component and extracts the beat locations as local extrema. The correct source for analyzing and computing the duration of individual beats is chosen by examining the frequency spectra and selecting the source with the clearest main frequency. Average pulse rate is identified using this frequency. For more fine-grained analysis and calculation of beat durations, peak detections are performed in the time domain.  

Problem Addressed 

Heart rate is a critical vital sign for medical diagnosis. There is a growing interest in extracting it without contact, particularly for populations such as premature neonates and the elderly who have fragile skin that may be damaged by traditional sensors. Furthermore, as the population ages, frequent monitoring outside of clinical environments can provide doctors with not just timely samples but also long-term trends and statistical analyses. This continuous monitoring requires a non-obtrusive technology. The Inventors have developed one such method of non-invasive heart monitoring by detecting pulse from head motions in video.  

Advantages

• Non-invasive, non-obtrusive method for continuous heart monitoring
• Can be used as a diagnosis tool for patients for whom traditional heart monitoring methods might be risky, including premature neonates and the elderly