PURPOSE

Timely and accurate triage of upper extremity injuries is critical, but current perfusion monitoring technologies have shortcomings. These limitations are especially pronounced in patients with darker skin tones. This pilot study evaluates a Eulerian Video Magnification (EVM) algorithm combined with color channel waveform extraction to enable video-based measurement of hand and finger perfusion.

METHODS

Videos of 10 volunteer study participants with Fitzpatrick skin types III-VI were taken in a controlled environment during normal perfusion and tourniquet-induced ischemia. Videos were EVM processed, and red/green/blue color channel characteristics were extracted to produce waveforms. These videos were assessed by surgeons with a range of expertise in hand injuries. The videos were randomized and presented in 1 of 3 ways: unprocessed, EVM processed, and EVM with waveform output (EVM+waveform). Survey respondents indicated whether the video showed an ischemic or perfused hand or if they were unable to tell. We used group comparisons to evaluate response accuracy across video types, skin tones, and respondent groups.

RESULTS

Of the 51 providers to whom the surveys were sent, 25 (49%) completed them. Using the Pearson χ test, the frequencies of correct responses were significantly higher in the EVM+waveform category than in the unprocessed or EVM videos. Additionally, the agreement was higher among responses to the EVM+waveform questions than among responses to the unprocessed or EVM processed. The accuracy and agreement from the EVM+waveform group were consistent across all skin pigmentations evaluated.

CONCLUSIONS

Video-based EVM processing combined with waveform extraction from color channels improved the surgeon's ability to identify tourniquet-induced finger ischemia via video across all skin types tested.

CLINICAL RELEVANCE

Eulerian Video Magnification with waveform extraction improved the assessment of perfusion in the distal upper extremity and has potential future applications, including triage, postsurgery vascular assessment, and telemedicine.