Background:Rounded shoulder posture (RSP), a postural abnormality, might cause shoulder pain and pathologic conditions. Although most previous research has investigated RSP focusing on the proximal structures of the shoulder, such as the scapula and pectoralis muscles, the relationship between RSP and anterior distal structures of the upper extremity, such as the biceps brachii muscle and elbow joint, is not clearly understood.Objects:This study aimed to investigate the correlations between RSP and the biceps brachii length, elbow joint angle (EJA), pectoralis minor length, general pectoralis major length, humeral head anterior translation (HHAT), glenohumeral internal rotation (IR), external rotation (ER), and horizontal adduction (HAD).Methods:Twelve subjects with RSP (6 male, 6 female) were recruited. All subjects fulfilled the RSP criteria indicated by a distance ≥2.5 cm from the posterior aspect of the acromion to the table in the supine position. The examiner measured each of the following parameters twice: RSP, biceps brachii length, EJA, pectoralis minor length, pectoralis major length, HHAT, glenohumeral IR, ER, and HAD. Pearson’s correlation coefficient(r) was used to assess the correlation between RSP and all the variables.Results:There was a significant moderate positive correlation between RSP and biceps brachii length (r=.55, p=.032), moderate negative correlation between RSP and pectoralis minor length (r=-.62, p=.015), and moderate positive correlation between RSP and HHAT (r=.53, p=.038).Conclusion:The biceps brachii length, pectoralis minor length, and HHAT could be used to evaluate patients with RSP. Better understanding of the correlation between these factors and RSP could help in the development of effective methods to treat patients with this condition in clinical management.

In this paper, the prototype of surface EMG (ElectroMyoGram) sensor is developed for the robotic rehabilitation applications, and the developed sensor is composed of the electrodes, analog signal amplifiers, analog filters, ADC (analog to digital converter), and DSP (digital signal processor) for coding the application example. Since the raw EMG signal is very low voltage, it is amplified by about one thousand times. The artifacts of amplified EMG signal are removed by using the band-pass filter. Also, the processed analog EMG signal is converted into the digital form by using ADC embedded in DSP. The developed sensor shows approximately the linear characteristics between the amplitude values of the sensor signals measured from the biceps brachii of human upper arm and the joint angles of human elbow. Finally, to show the performance of the developed EMG sensor, we suggest the application example about the real-time human elbow motion acquisition by using the developed sensor.