The purpose of the present study was to investigate motor unit (MU) recruitment and firing rate, and the MU action potential (MUAP) characteristics of the human supraspinatus muscle during prolonged static contraction and subsequent recovery. Eight female subjects sustained a 30 degrees shoulder abduction, requiring 11-12% of maximal voluntary contraction (MVC), for 30 min. At 10 and 30 min into the recovery period, the shoulder abduction was repeated for 1 min. The rating of perceived exertion for the shoulder region increased to "close to exhaustion" during the prolonged contraction, and the surface electromyography (EMG) recorded from the deltoid and trapezius muscles showed signs of local muscle fatigue. From the supraspinatus muscle, a total of 23,830 MU firings from 265 MUs were identified using needle electrodes. Of the identified MUs, 95% were continuously active during the 8-s recordings, indicating a low degree of MU rotation. The mean (range) MU firing rate was 11.2 (5.7-14.5) Hz, indicating the relative force contribution of individual MUs to be larger than the overall mean shoulder muscle load. The average MU firing rate remained stable throughout the prolonged abduction, although firing rate variability increased in response to fatigue. The average concentric MUAP amplitude increased by 38% from the beginning (0-6 min) to the end (24-29 min) of the contraction period, indicating recruitment of larger MUs in response to fatigue. In contrast, after 10 min of recovery the average MU amplitude was smaller than seen initially in the prolonged contraction, but not different after 30 min, while the MU firing rate was higher during both tests. In conclusion, MU recruitment plays a significant role during fatigue, whereas rate coding has a major priority during recovery. Furthermore, a low degree of MU rotation in combination with a high relative load at the MU level may imply a risk of overloading certain MUs during prolonged contractions.

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Musculoskeletal symptoms among computer users are frequently found. The aim was to investigate the musculoskeletal workload during computer work using speech recognition and traditional computer input devices (keyboard/mouse). Ten experienced computer users (nine female, one male) participated. They performed three different computer tasks: (1). text entry and (2). text editing of a standard text and (3). a self-selected work task. These tasks were performed twice using speech recognition and traditional computer input devices (keyboard/mouse). Additionally, a task consisting of reading aloud of the standard text was performed. Surface EMG from the forearm (m. extensor carpi ulnaris, m. extensor carpi radialis), the shoulder (m. trapezius) and the neck extensor muscles was recorded, in addition to the voice-related muscles (m. scalenii, m. cricothyroideus). Using speech recognition during text entry and text editing reduced the static muscle activity of the forearm, neck and to some extent the shoulder muscles. Furthermore, tendencies to longer periods of muscle activity pause (relative time with EMG gaps) in the forearm and shoulder muscles were found. This was seen at the expense of a tendency to an increased static activity and a decreased relative time with EMG gaps in m. cricothyroideus. Finally, during use of speech recognition the hand was tied to the keyboard/mouse for a shorter period of time, while the eyes were viewing the screen for a longer period of time compared to the condition with traditional computer input devices. It is recommended to use speech recognition as a supplementary tool to traditional computer input devices.