## 4 Discussion  
All current CPM machines can only move the patient's leg passively without requiring any interaction initiated by the patients [17]. To incorporate human-machine interaction into this technology, the traditional control system of the CPM machine was changed to utilise the EMG biofeedback signals in this study. This project was a preliminary study that used EMG signals to drive a CPM machine, suggesting that this horizontal EMG-based control system could assist bedridden patients with severe muscle weakness in rehabilitation. As previously mentioned, [PERSON] and [PERSON] (2009) developed a motorised CPM/CAM knee joint that could provide active resistance to oppose the motion of the user by way of a force sensor under the patient's foot pedal [10]. Their device could be suitable for patients in the advanced stages of rehabilitation who have had knee replacement surgery. However, adding an EMG signal control to the device would constitute a more interactive and effective approach since it directly reflects the intention of movement; also, it could be suitable for neuromuscular patients with severe weakness of the lower limbs in the early stages of rehabilitation.  
Some previous research groups have designed their own EMG interface system instead of using the TrignoTM system. TrignoTM has a high cost; however, it helps to simplify the interface circuit. According to previous studies, without the TrignoTM system, researchers had to build an external amplification circuit followed by a filter circuit [18; 19; 20]. In this study, eight EMG signals were used for a comprehensive measure of muscle movements. In that case, eight amplification circuits need to be implemented, in addition to eight filter circuits to avoid noises, which made the design more complex and increased the possibility of signal interference and noise. Because the TrignoTM EMG system has its own internal amplification circuit, the signal is clearer, avoiding noise, and the circuit is simplified.  
According to the previous studies, there is a limitation with the number of EMG signals because of the design of external amplification and filter circuits. For the present study, researchers looked for a sufficient microcontroller that would offer a highly stable  
Figure 21: The actual view of connection during the experiment.  
performance. By considering other studies [21; 22], it was found that using Arduino UNO with an ATMEGA microcontroller may have limitations with the functions of clock performance in getting an accurate output value with a high response. In addition, there were a limited number of input and output ports. For example, according to [21], which studied controlling the movement of a wheelchair using EMG signals collected from the arm, they used two Arduino UNO microcontrollers, one for collecting the EMG signals and another Arduino UNO for sending the signals to the actuator. While in the present study, researchers only used one microcontroller \"STM32\" that collected EMG signals and sent the required signal to the actuator simultaneously.  
The reliability of the proposed system was validated, and overall, the results confirm high reliability of the developed interface system when compared with the EMG output data of the Delsys(r) and Vicon(r) systems. The findings show that there were constant differences in amplitude values between both systems. The proposed system had slightly higher values than the Delsys(r) and Vicon(r) systems, within an average rate of 0.00187 V. In other words, the systematic shifting value between both systems was 0.00187 V, and when this value is subtracted from the proposed system's EMG reading, both systems have the same amplitude values. The results obtained show that the developed instrument could work as a controller interface between EMG and a CPM medical device that needs to use EMG for its function.