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</script>pmid: 18636978
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.
Male, Biometry, Photogrammetry, Posture, Humans, Videotape Recording, Forensic Medicine, Gait, Security Measures, Biomechanical Phenomena
Male, Biometry, Photogrammetry, Posture, Humans, Videotape Recording, Forensic Medicine, Gait, Security Measures, Biomechanical Phenomena
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 131 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
