When using wearable sensors for measurement and analysis of human performance, it is often necessary to integrate and synchronise data from separate sensor systems. This paper describes a synchronization technique between IMUs attached to the shanks and insoles attached at the feet and aims to solve the need to compute the ankle joint angle, which relies on synchronized sensor data. This will additionally enable concurrent analysis using gait kinematic and kinetic features. A proof-of-concept of the algorithm, which relies on cross-correlation of gyroscope sensor data from the shank and foot, to align the sensor systems is demonstrated. The algorithm output is validated against those signals synchronized using manually annotated heel-strike and toe-off ground-truth signal landmarks, identified in both the shank and feet signals using previously published definitions. Results demonstrate that the developed algorithm is capable of synchronizing both sensor systems, based on IMU data from both healthy participants and participants suffering from knee osteoarthritis, with a mean lag time bias of 25.56ms when compared to the ground truth. A proof-of-concept of technique to synchronise IMUs attached to the shanks and insoles attached at the feet is demonstrated and offers an alternative approach to sensor system synchronisation.