Literature DB >> 18636978

Gait analysis in forensic medicine*.

Peter K Larsen1, Erik B Simonsen, Niels Lynnerup.   

Abstract

Recordings from video surveillance systems are used as evidence from crime scenes. It would be useful to perform comparisons between disguised perpetrators and suspects based on their gait. We applied functional anatomical and biomechanical knowledge to analyze the gait of perpetrators, as recorded on surveillance video. Using a structured checklist, which addresses the single body segments during gait, we were able to give a statement concerning the gait patterns. Characteristic parameters were, e.g., varus instability in the knee at heel strike, and larger lateral flexion of the spinal column to one side than the other. Based on these characteristic features, we are able to state with reasonable certainty whether the suspect could be the perpetrator, but it is not possible to identify the perpetrator positively. Nevertheless, we have been involved in several cases where the court has found that this type of gait analysis was a valuable tool.

Mesh:

Year:  2008        PMID: 18636978     DOI: 10.1111/j.1556-4029.2008.00807.x

Source DB:  PubMed          Journal:  J Forensic Sci        ISSN: 0022-1198            Impact factor:   1.832


  13 in total

1.  A new atlas for the evaluation of facial features: advantages, limits, and applicability.

Authors:  Stefanie Ritz-Timme; Peter Gabriel; Zuzana Obertovà; Melanie Boguslawski; F Mayer; A Drabik; Pasquale Poppa; Danilo De Angelis; Romina Ciaffi; Benedetta Zanotti; Daniele Gibelli; Cristina Cattaneo
Journal:  Int J Legal Med       Date:  2010-04-06       Impact factor: 2.686

2.  Comparing the face to the body, which is better for identification?

Authors:  Teghan Lucas; Maciej Henneberg
Journal:  Int J Legal Med       Date:  2015-02-10       Impact factor: 2.686

3.  Forensic 3D documentation of skin injuries.

Authors:  Chiara Villa
Journal:  Int J Legal Med       Date:  2016-12-02       Impact factor: 2.686

4.  A View Transformation Model Based on Sparse and Redundant Representation for Human Gait Recognition.

Authors:  Abbas Ghebleh; Mohsen Ebrahimi Moghaddam
Journal:  J Med Signals Sens       Date:  2020-07-03

5.  Independent contributions of the face, body, and gait to the representation of the whole person.

Authors:  Noa Simhi; Galit Yovel
Journal:  Atten Percept Psychophys       Date:  2021-01       Impact factor: 2.199

6.  Gait recognition using a few gait frames.

Authors:  Lingxiang Yao; Worapan Kusakunniran; Qiang Wu; Jian Zhang
Journal:  PeerJ Comput Sci       Date:  2021-03-01

7.  Comparative Study of Markerless Vision-Based Gait Analyses for Person Re-Identification.

Authors:  Jaerock Kwon; Yunju Lee; Jehyung Lee
Journal:  Sensors (Basel)       Date:  2021-12-08       Impact factor: 3.576

8.  A Low-Cost, Autonomous Gait Detection and Estimation System for Analyzing Gait Impairments in Mice.

Authors:  Pranav U Damale; Edwin K P Chong; Sean L Hammond; Ronald B Tjalkens
Journal:  J Healthc Eng       Date:  2021-11-12       Impact factor: 2.682

Review 9.  Critical review of the use and scientific basis of forensic gait analysis.

Authors:  Nina M van Mastrigt; Kevin Celie; Arjan L Mieremet; Arnout C C Ruifrok; Zeno Geradts
Journal:  Forensic Sci Res       Date:  2018-10-09

10.  Uniqueness of gait kinematics in a cohort study.

Authors:  Gunwoo Park; Kyoung Min Lee; Seungbum Koo
Journal:  Sci Rep       Date:  2021-07-27       Impact factor: 4.379

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