Events and phases detection of the human gait are vital for controlling prosthesis, orthosis and functional electrical stimulation (FES) systems. Wearable sensors are inexpensive, portable and have fast processing capability. They are frequently used to assess spatio-temporal, kinematic and kinetic parameters of the human gait which in turn provide more details about the human voluntary control and ampute-eprosthesis interaction. This paper presents a reliable real-time gait event detection algorithm based on simple heuristics approach, applicable to signals from tri-axial gyroscope for lower limb amputees during ramp ascending and descending. Experimental validation is done by comparing the results of gyroscope signal with footswitches. For healthy subjects, the mean difference between events detected by gyroscope and footswitches is 14 ms and 10.5 ms for initial contact (IC) whereas for toe off (TO) it is -5 ms and -25 ms for ramp up and down respectively. For transfemoral amputee, the error is slightly higher either due to the placement of footswitches underneath the foot or the lack of proper knee flexion and ankle plantarflexion/dorsiflexion during ramp up and down. Finally, repeatability tests showed promising results.