Powered exoskeleton technology helps turns dreams of recovering mobility after paralysis into reality. One of the most common problems encountered in the use of powered exoskeletons is the detection of the motion intentions of the user. Many approaches to conquering this problem have been developed using Electromyography (EMG) sensors, Electroencephalography (EEG) sensors, Center of Pressure (COP), and so forth. When a method, such as the surface EMG, is contaminated with noise during acquisition, it is important to process that raw EMG signal. Doing so usually takes time, and time delays in such a system can lead to a loss in synchronization between the wearer and the exoskeleton. Many algorithms have been developed for data acquisition and the filtering of raw EMG signals as well as accelerometer data. Our approach involves designing an almost sensor-less low limb exoskeleton that is powered by an electric Direct Current (DC) motor, and the same motor is used to detect motion via monitoring the voltage and the current variation. Experimental results are obtained for the actuating knee flexion-to-extension then extension-to-flexion of a sitting person using the National Instrument (NI) MyRIO as a data acquisition system with NI-LabView. The results support the hypothesis that the developed system can detect human motion and drive the motor in the necessary direction without the use of uncomfortable electrodes (sensors) and their connections. Additionally, the system supported the wearer to move his leg up (extension) without having too much effort to do so. In order to identify muscle activation with the change in the angle along the sagittal plane, an accelerometer has been attached to the system. The proposed approach could help open a new pathway along which researchers could develop low-cost and easy-to-wear powered exoskeletons which could emulate precisely the normal gait of a human.