Gait Analysis Emerges as Crucial Forensic Tool in Pune Murder Investigation as Traditional Identification Methods Fail

Gait Analysis Emerges as Crucial Forensic Tool in Pune Murder Investigation as Traditional Identification Methods Fail

Gait analysis has emerged as a critical forensic tool in the Pune murder investigation after investigators found conventional identification methods ineffective. Police say Artificial Intelligence-powered gait recognition can identify suspects through unique walking patterns and is becoming increasingly important in complex criminal cases where digital and visual evidence is deliberately concealed.

 

The ongoing investigation into the Pune murder case has brought renewed attention to gait analysis, an advanced forensic technique that identifies individuals through their distinctive walking pattern. Investigators believe the technology could play a decisive role in solving cases where conventional identification methods, including facial recognition and mobile phone tracking, become ineffective because suspects deliberately eliminate digital and visual evidence.

Speaking on the significance of gait analysis in the Pune murder investigation, Sambhal Superintendent of Police Krishna Kumar Bishnoi said the accused had carefully planned the crime by neutralising the conventional clues normally used by investigators.

"Traditional identification methods such as facial recognition and phone triangulation are ineffective because the accused deliberately eliminated these elements as part of a well-planned strategy. The most effective way for investigators to establish the case is through gait pattern analysis, one of the strongest forms of forensic evidence. Every individual has a unique walking pattern," Bishnoi said.

Gait analysis examines an individual's manner of walking by studying multiple characteristics, including stride length, walking speed, posture, arm movement, foot placement and overall body mechanics. These behavioural and biomechanical features are compared with surveillance camera footage and controlled recordings of a suspect to determine whether the movement patterns correspond.

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According to Bishnoi, recent advances in Artificial Intelligence have significantly enhanced the accuracy and reliability of gait analysis. Earlier, forensic experts manually examined surveillance footage frame by frame, making the process both time-consuming and heavily dependent on human observation. Today, Artificial Intelligence-powered computer vision systems can automatically extract biometric characteristics such as stride duration, posture and body movement to generate a unique gait profile for comparison.

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He further stated that every individual demonstrates a repetitive and distinctive gait pattern, enabling investigators to identify a person from a distance solely through the way they walk.

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The forensic technique has already played an important role in several high-profile criminal investigations across India. One of the most notable examples was the 2017 murder of journalist and activist Gauri Lankesh in Bengaluru. Because the assailant concealed his face with a helmet, investigators were unable to rely on facial identification. Following the arrest of accused Parashuram Waghmore, the Karnataka Special Investigation Team recreated the crime scene and recorded his movements while he wore clothing similar to that seen in the surveillance footage. Forensic experts subsequently compared his gait with the recorded footage, and the findings became a significant piece of corroborative evidence during the investigation.

Gait analysis was also employed during the investigation into the 2021 Saki Naka rape and murder case in Mumbai, further demonstrating its growing importance in complex criminal investigations where suspects attempt to conceal their identities.

Forensic experts, however, emphasise that gait analysis is generally treated as corroborative evidence rather than conclusive proof. It is used alongside surveillance footage, forensic examinations, witness statements and other scientific evidence to strengthen an investigation and support the overall case.

As criminals increasingly use face coverings, avoid carrying mobile phones and attempt to erase their digital footprints, gait analysis is becoming an increasingly valuable forensic resource for law enforcement agencies. With continuing advancements in Artificial Intelligence and computer vision technologies, investigators are expected to rely more extensively on gait analysis in cases where traditional identification techniques are unable to establish the identity of a suspect, reinforcing its growing role in modern criminal investigations.

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