The Modified Ashworth Scale (MAS) is commonly used to assess spasticity in clinics. The qualitative description of MAS has resulted in ambiguity during spasticity assessment. This work supports spasticity assessment by providing measurement data acquired from wireless wearable sensors, i.e., goniometers, myometers, and surface electromyography sensors. Based on in-depth discussions with consultant rehabilitation physicians, eight (8) kinematic, six (6) kinetic, and four (4) physiological features were extracted from the collected clinical data from fifty (50) subjects. These features were used to train and evaluate the conventional machine learning classifiers, including but not limited to Support Vector Machine (SVM) and Random Forest (RF). Subsequently, a spasticity classification approach combining the decision-making logic of the consultant rehabilitation physicians, SVM, and RF was developed. The empirical results on the unknown test set show that the proposed Logical–SVM–RF classifier outperforms each individual classifier, reporting an accuracy of 91% compared to 56–81% achieved by SVM and RF. A data-driven diagnosis decision contributing to interrater reliability is enabled via the availability of quantitative clinical data and a MAS prediction.

There are different styles of lifting objects of the ground, and each style gives out different percentage of contribution of each muscle. The purpose of this study is to investigate the muscle activity between stooping and squatting to avoid low back pain and how the muscle activities differ from a correct technique of squatting, and an incorrect one. The Rectus Abdominis, Erector Spinae, Quadriceps and Hamstrings muscle were chosen to be monitored for differences in this study. Selected subjects were two healthy males, with the same height and age, one subject has no experience in doing squats – define as amateur, and the other subject know the basic method of squat-ting – define as non-amateur. In order to capture and analyze the activity of the muscles, Myon EMG and ProEMG software were used. Participants performed, stooping and squatting movement for 12 repetitions with 5 minutes’ rest in between. The muscle activation strength was obtained by calculating the Root Mean Square of the EMG data. Results shows that the non-amateur gave out greater RMS difference in muscle activation for the Erector Spinae and Rectus Abdominis among other muscles compared to amateur for both stooping and squatting. Another finding was that, the results of a non-amateur were more balanced between both left and right muscles activation compared to the amateur subject. These observations raised the need of mind muscle connection and muscle coordination in order to lift efficiently in order to avoid low back injury.

The purpose of electromyography (EMG) study is to identify which position of surface EMG sensor attached to erector spinae muscle related with lower back pain by squat and stoop lifting technique. This is to avoid lower back pain (LBP) occur during Manual Materials Handling (MMH). There are only one types of upper extremity muscle were chosen to be monitored in this study which is erector spinae (ES) muscle with different electrodes placement on the surface electromyography (sEMG) sensor. However, each of the lifting styles come out with the different reading of root mean square (RMS) frequency for each muscle chosen. In this study, the two subjects consist of two females with normal body mass index (BMI) range from 18.5 to 24.9 with same physical measurement, was selected in order to perform both styles of lifting which are squatting and stooping. For every session the subject will undertake 15 repetitions with 15 minutes rest in between for each movement. In furtherance of to get the analysis muscle activity, proEMG software is used. The results of study for subject female 1 showed that the squat technique had higher levels of muscle activation compared to stoop technique on left erector spinae (LES) muscle. However, the LES muscle activation for subject 2 is greater at stoop activity. On the contrary, squat technique had lower fatigue analysis compared to stoop technique for both subjects on LES muscle. Conclusion, squat technique is better than stoop technique but stoop lift is more natural and spontaneously used for MMH.