BACKGROUND: Whole-body vibration (WBV) is a neuromuscular training method that has recently received popularity in health and fitness centers, as an additional or substitute method to conventional training and therapy, in order to improve muscle stre

Bio-signals are distinctive factors in the design of the human-machine interface, essentially useful for prosthesis, orthosis, and exoskeletons. Despite the progress in the analysis of pattern recognition based devices; the acceptance of these devices is still questionable. One reason is the lack of information to identify the possible combinations of features and classifiers. Besides; there is also a need for optimal selection of various sensors for sensations such as touch, force, texture, along with EMGs/EEGs. This paper reviews the two bio-signal techniques, named as electromyography and electroencephalography. The details of the features and the classifiers used in the data processing for upper limb assist devices are summarised here. Various features and their sets are surveyed and different classifiers for feature sets are discussed on the basis of the classification rate. The review was carried out on the basis of the last 10-12 years of published research in this area. This paper also outlines the influence of modality of EMGs and EEGs with other sensors on classifications. Also; other bio-signal used in upper limb devices, and the future aspects are considered in this paper.

The aim of the study was to examine the pattern of the change in discomfort for combined wrist deviation and forearm rotation as joint angles increased away from neutral in a repetitive task. There were five levels of wrist deviation (neutral, 35% and 55% of the range of motion (ROM) in radial and ulnar deviation) and five levels of forearm rotation (neutral, 30% and 60% of the ROM in pronation and supination). Twenty-five participants performed a repetitive flexion task with a force of 10 N ± 1 N at a frequency of 15 exertions per min, with replication after 1 week for six of the participants. A visual analogue scale was used for recording the discomfort scores. Repeated measures analysis of covariance with the Greenhouse-Geisser correction, where necessary, was used on transformed values of the discomfort scores. Grip test endurance time at 50% of maximum voluntary contraction was included as a covariate. Wrist deviation (p = 0.007) and forearm rotation (p = 0.001) were found to have significant effects. Interactions of the main factors were not significant and nor was the covariate. Quadratic regression equations were derived and were used to generate iso-discomfort contours, which show a useful area of low discomfort around the central neutral zone of wrist postures, but with steep increases in discomfort at the extreme combinations of wrist ulnar/radial deviation with forearm pronation/supination. Discomfort equations and contours, showing wrist and forearm postures, which are either acceptable or potentially injurious, are useful for the design of industrial tools, machine controls and workspaces. Reference to these can help to reduce the risk of musculoskeletal injury associated with the tasks or tools by avoiding poor postures with unacceptable deviations from neutral posture.

This study investigated perceived discomfort in an isometric wrist flexion task. Independent variables were wrist flexion/extension (55%, 35% flexion, neutral, 35% and 55% extension ranges of motion (ROM)), forearm rotation (60%, 30% prone, neutral, 30% and 60% supine ROM) and two levels of flexion force (10% and 20% maximum voluntary contraction (MVC)). Discomfort was significantly affected by flexion force, forearm rotation and a two-way interaction of force with forearm rotation (each p < 0.05). High force for 60%ROM forearm pronation and supination resulted in increasingly higher discomfort for these combinations. Flexion forces were set relative to the MVC in each wrist posture and this appears to be important in explaining a lack of significant effect (p = 0.34) for flexion/extension on discomfort. Regression equations predicting discomfort were developed and used to generate iso-discomfort contours, which indicate regions where the risk of injury should be low and others where it is likely to be high. Regression equations predicting discomfort and iso-discomfort contours are presented, which indicate combinations of upper limb postures for which discomfort is predicted to be low, and others where it is likely to be high. These are helpful in the study of limits for risk factors associated with upper limb musculoskeletal injury in industry.