Foot Strike Pattern Detection Using a Loadsol^® Sensor Insole.

Area of Science:

• Biomechanics
• Sports Medicine
• Wearable Technology

Background:

• Running-related injuries are common and linked to foot strike patterns (FSP).
• Accurate FSP detection is crucial for understanding injury mechanisms and prevention strategies.
• Existing methods for FSP analysis may have limitations in real-world applications.

Purpose of the Study:

• To investigate the efficacy of the loadsol® sensor insole for detecting FSP during treadmill running.
• To compare the loadsol® sensor's FSP detection with a traditional kinematic method.
• To assess the variability of FSP across different running speeds.

Main Methods:

• Twelve collegiate athletes performed treadmill running at 12, 15, and 20 km/h.
• Foot strike patterns were determined using both kinematic analysis (foot strike angle) and the loadsol® sensor insole (plantar force distribution).
• Detection rates for rearfoot, midfoot, and forefoot strikes were calculated and compared between methods.

Main Results:

• The loadsol® sensor demonstrated high detection rates for rearfoot (94.7%) and forefoot (81.8%) strikes, with lower accuracy for midfoot strikes (37.1%).
• Foot strike patterns were not consistent, with most participants exhibiting mixed patterns even at constant speeds.
• Significant variations in FSP were observed across different running speeds.

Conclusions:

• The loadsol® sensor insole presents a viable tool for in-field FSP measurement and impact force analysis.
• This technology can aid researchers and athletes in understanding running biomechanics and predicting injury risks.
• Monitoring step-to-step FSP variations offers potential for personalized injury prevention.