Manual Whisker Annotator (MWA): A Modular Open-Source Tool

Authors

  • Brett M. Hewitt Division of Biology and Conservation Ecology and Division of Computer Science and Information Systems, Manchester Metropolitan University https://orcid.org/0000-0003-2348-7600
  • Moi Hoon Yap Division of Computer Science and Information Systems, Manchester Metropolitan University https://orcid.org/0000-0001-7681-4287
  • Robyn A. Grant Division of Biology and Conservation Ecology, Manchester Metropolitan University

DOI:

https://doi.org/10.5334/jors.93

Keywords:

Whisker, Annotator, Manual, Tracker, Curvature, Angle, Velocity, Animal Behaviour, Computer Vision, Analysis

Abstract

Rodents are key to generating translational data for healthcare research. Behavioural analyses, in particular, are integral to the non-invasive monitoring of rodent health and welfare. Finding quantitative behavioural measures mitigates stress, allowing for the animal behave freely while also enabling the same animal to be studied over the time-course of its life. Locomotion and whisking are both such quantitative behavioural measures, and have been found to be significantly impacted in rodent models of neurodegenerative disease. While automatic trackers of whiskers and locomotion exist, a manual tracker is required to validate these approaches, and also to annotate complex videos where these automatic versions fail. Manually annotating whiskers for research purposes is a long and tedious task and current software does little to provide an intuitive and simple interface to carry out this task. This led to the creation of the Manual Whisker Annotator (MWA). MWA is an open source, portable whisker annotation tool developed for the Windows platform. Not only does MWA make the process much quicker, it also provides added statistical tools to analyse the data. MWA was developed in C# and WPF using the .NET framework, and could be used in any situation where annotating or tracking multiple targets is desired.

Author Biographies

Brett M. Hewitt, Division of Biology and Conservation Ecology and Division of Computer Science and Information Systems, Manchester Metropolitan University

Currently studying for my PhD at Manchester Metropolitan University, my main focus is on using Computer Vision to aid Biological research.

Moi Hoon Yap, Division of Computer Science and Information Systems, Manchester Metropolitan University

Moi Hoon Yap received her PhD in Computer Science from Loughborough University in 2009. She received her BSc (hons) in Statistics (1999) and MSc IT (2001) from Universiti Putra Malaysia (UPM). After her PhD, she worked as Postdoctoral Research Assistant (April 09 - Oct 11) in the Centre for Visual Computing, University of Bradford, UK. Currently, she is a Senior lecturer in Faculty of Science and Engineering, Manchester Metropolitan University, UK. She is actively involved in computer vision research. Her research interests are facial analysis, medical image analysis, using technology for dementia care, image and video processing.

Robyn A. Grant, Division of Biology and Conservation Ecology, Manchester Metropolitan University

Division of Biology & Conservation Ecology My research has mainly focussed on characterising the behaviour and physiology of whisker touch systems in mammals. Specific projects I am involved in are: Comparative physiology of whisker touch including whisker muscle studies in collaboration with the Weizmann Institute, Israel. Comparative active touch behaviours focusing on rats, mice, dormice, opossums, harbour seals, sealions and humans; in collaboration with the University of Sheffield, UK, Wildwood Trust, UK, Blackpool Zoo, UK and the Marine Science Center, Germany. Evolution of sensing strategies with a focus on rodents, in collaboration with Wildwood Trust, Kent, UK and Dr Matthew Sullivan, MMU Behavioural measures of disease with a focus on motor neuron disease and aging in collaboration with the Department of Neuroscience at the University of Sheffield, UK Species sensory capabilities and conservation Bio-inspired robotics Video analysis tools for measuring behaviour Development of sensing strategies

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Published

2016-04-28

Issue

Vol. 4 No. 1 (2016)

Section

Software Metapapers

License

Copyright (c) 2016 The Author(s)

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