Back injuries are the most prevalent work-related musculoskeletal disorders and represent a major cause of disability and socio-economic problems. Although innovations in wearable robots aim to alleviate this hazard, the majority of existing exoskeletons are obtrusive because the rigid linkage design limits natural movement, thus causing ergonomic risk. Moreover, these existing systems are typically only suitable for one type of movement assistance, not ubiquitous for a wide variety of activities. To fill in this gap, this paper presents a new wearable robot design approach continuum soft exoskeleton. This wearable robot is unobtrusive and assists both squat and stoops while not impeding walking motion. To tackle the challenge of the unique anatomy of spine, our robot is conformal to human anatomy and it can reduce multiple types of forces along the human spine such as the spinae muscle force, shear, and compression force of the lumbar vertebrae. We derived kinematics and kinetics models of this mechanism and established an analytical biomechanics model of human-robot interaction. Quantitative analysis of disc compression force, disc shear force and muscle force was performed in simulation. We further developed a virtual impedance control strategy to deliver force control and compensate hysteresis of Bowden cable transmission. The feasibility of the prototype was experimentally tested on three healthy subjects. The root mean square error of force tracking is 6.63 N (3.3 % of the 200N peak force) and it demonstrated that it can actively control the stiffness to the desired value. This continuum soft exoskeleton represents a feasible solution with the potential to reduce back pain for multiple activities and multiple forces along the human spine.

The purpose of this study was to compare the effect of training using internal imagery (IMI; also known as kinesthetic imagery or first person imagery) with that of external imagery (EMI; also known as third-person visual imagery) of strong muscle contractions on voluntary muscle strengthening. Eighteen young, healthy subjects were randomly assigned to one of three groups (6 in each group): internal motor imagery (IMI), external motor imagery (EMI), or a no-practice control (CTRL) group. Training lasted for 6 weeks (~15 min/day, 5 days/week). The participants’ right arm elbow-flexion strength, muscle electrical activity and movement-related cortical potential (MRCP) were evaluated before and after training. Only the IMI group showed significant strength gained (10.8%) while the EMI (4.8%) and CTRL (-3.3%) groups did not. Only the IMI group showed a significant elevation in MRCP on scalp locations over both the primary motor (M1) and supplementary motor cortices (EMI group over M1 only) and this increase was significantly greater than that of EMI and CTRL groups. These results suggest that training by IMI of forceful muscle contractions was effective in improving voluntary muscle strength without physical exercise. We suggest that the IMI training likely strengthened brain-to-muscle (BTM) command that may have improved motor unit recruitment and activation, and led to greater muscle output. Training by internal motor imagery of forceful muscle contractions may change the activity level of cortical motor control network, which may translate into greater descending command to the target muscle and increase its strength.