Citation: Järemo Lawin, F; Byström, A.; Roepstorff, C.; Rhodin, M.; Almlöf, M.; Silva, M.; Andersen, P.H.; Kjellström, H.; Hernlund, E. Is Markerless More or Less? Comparing a Smartphone Computer Vision Method for Equine Lameness Assessment to Multi-Camera Motion Capture. Animals 2023, 13, 390. https://doi.org/10.3390/ ani13030390 Academic Editor: Lindsay St. George Received: 19 November 2022 Revised: 10 January 2023 Accepted: 13 January 2023 Published: 24 January 2023 Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). animals Article Is Markerless More or Less? Comparing a Smartphone Computer Vision Method for Equine Lameness Assessment to Multi-Camera Motion Capture Felix Järemo Lawin 1 , Anna Byström 2 , Christoffer Roepstorff 1 , Marie Rhodin 2 , Mattias Almlöf 1 , Mudith Silva 1 , Pia Haubro Andersen 2 , Hedvig Kjellström 3 and Elin Hernlund 1,2, * 1 Sleip AI, Birger Jarlsgatan 58, 11426 Stockholm, Sweden; felix@sleip.com (F.J.L.); christoffer@sleip.com (C.R.); mattias@sleip.com (M.A.); mudith@sleip.com (M.S.) 2 Department of Anatomy, Physiology and Biochemistry, Swedish University of Agricultural Sciences, 75007 Uppsala, Sweden; elin.hernlund@slu.se (E.H.); anna.bystrom@slu.se (A.B.); marie.rhodin@slu.se (M.R.); pia.haubro.andersen@slu.se (P.H.A.) 3 KTH Royal Institute of Technology, Division of Robotics, Perception and Learning, 10044 Stockholm, Sweden; hedvig@kth.se * Correspondence: elin.hernlund@slu.se; Tel.: +46-18-672142 Simple Summary: Lameness, an alteration of the gait due to pain or dysfunction of the locomotor system, is the most common disease symptom in horses. Yet, it is difficult for veterinarians to correctly assess by visual inspection. Objective tools that can aid clinical decision making and provide early disease detection through sensitive lameness measurements are needed. In this study, we describe how an AI-powered measurement tool on a smartphone can detect lameness in horses without the need to mount equipment on the horse. We compare it to a state-of-the-art multi-camera motion capture system by simultaneous, synchronised recordings from both systems. The mean difference between the systems’ output of lameness metrics was below 2.2 mm. Therefore, we conclude that the smartphone measurement tool can detect lameness at relevant levels with easy-of-use for the veterinarian. Abstract: Computer vision is a subcategory of artificial intelligence focused on extraction of infor- mation from images and video. It provides a compelling new means for objective orthopaedic gait assessment in horses using accessible hardware, such as a smartphone, for markerless motion analy- sis. This study aimed to explore the lameness assessment capacity of a smartphone single camera (SC) markerless computer vision application by comparing measurements of the vertical motion of the head and pelvis to an optical motion capture multi-camera (MC) system using skin attached reflective markers. Twenty-five horses were recorded with a smartphone (60 Hz) and a 13 camera MC-system (200 Hz) while trotting two times back and forth on a 30 m runway. The smartphone video was processed using artificial neural networks detecting the horse’s direction, action and motion of body segments. After filtering, the vertical displacement curves from the head and pelvis were synchronised between systems using cross-correlation. This rendered 655 and 404 matching stride segmented curves for the head and pelvis respectively. From the stride segmented vertical displacement signals, differences between the two minima (MinDiff) and the two maxima (MaxDiff) respectively per stride were compared between the systems. Trial mean difference between systems was 2.2 mm (range 0.0–8.7 mm) for head and 2.2 mm (range 0.0–6.5 mm) for pelvis. Within-trial standard deviations ranged between 3.1–28.1 mm for MC and between 3.6–26.2 mm for SC. The ease of use and good agreement with MC indicate that the SC application is a promising tool for detecting clinically relevant levels of asymmetry in horses, enabling frequent and convenient gait monitoring over time. Keywords: monocular motion analysis; objective lameness assessment; equine orthopaedics; animal pose estimation; optical motion capture Animals 2023, 13, 390. https://doi.org/10.3390/ani13030390 https://www.mdpi.com/journal/animals