This paper presents a gait phase detection algorithm for providing feedback in walking with a robotic prosthesis. The algorithm utilizes the output signals of a wearable wireless sensory system incorporating sensorized shoe insoles and inertial measurement units attached to body segments. The principle of detecting transitions between gait phases is based on heuristic threshold rules, dividing a steady-state walking stride into four phases. For the evaluation of the algorithm, experiments with three amputees, walking with the robotic prosthesis and wearable sensors, were performed. Results show a high rate of successful detection for all four phases (the average success rate across all subjects >90%). A comparison of the proposed method to an off-line trained algorithm using hidden Markov models reveals a similar performance achieved without the need for learning dataset acquisition and previous model training.

Objective: To compare spinal manipulation, back school and individual physiotherapy in the treatment of chronic low back pain. Design: Randomized trial, 12-month follow-up. Setting: Outpatient rehabilitation department. Participants: 210 patients with chronic, non-specific low back pain, 140/210 women, age 59 ± 14 years. Interventions: Back school and individual physiotherapy scheduled 15 1-hour-sessions for 3 weeks. Back school included: group exercise, education/ ergonomics; individual physiotherapy: exercise, passive mobilization and soft-tissue treatment. Spinal manipulation, given according to Manual Medicine, scheduled 4 to 6 20’-sessions once-a-week. Outcome: Roland Morris Disability Questionnaire (scoring 0-24) and Pain Rating Scale (scoring 0-6) were assessed at baseline, discharge 3, 6, and 12 months. Results: 205 patients completed the study. At discharge, disability score decreased by 3.7 ± 4.1 for back school, 4.4 ± 3.7 for individual physiotherapy, 6.7 ± 3.9 for manipulation; pain score reduction was 0.9 ± 1.1, 1.1 ± 1.0, 1.0 ± 1.1, respectively. At 12 months, disability score reduction was 4.2 ± 4.8 for back school, 4.0 ± 5.1 for individual physiotherapy, 5.9 ± 4.6 for manipulation; pain score reduction was 0.7 ± 1.2, 0.4 ± 1.3, and 1.5 ± 1.1, respectively. Spinal manipulation was associated with higher functional improvement and long-term pain relief than back school or individual physiotherapy, but received more further treatment at follow-ups (P<0.001); pain recurrences and drug intake were also reduced compared to back school (P <0.05) or individual physiotherapy (P <0.001). Conclusions: Spinal manipulation provided better short and long-term functional improvement, and more pain relief in the follow-up than either back school or individual physiotherapy.

In human-centered robotics, exoskeletons are becoming relevant for addressing needs in the healthcare and industrial domains. Owing to their close interaction with the user, the safety and ergonomics of these systems are critical design features that require systematic evaluation methodologies. Proper transfer of mechanical power requires optimal tuning of the kinematic coupling between the robotic and anatomical joint rotation axes. We present the methods and results of an experimental evaluation of the physical interaction with an active pelvis orthosis (APO). This device was designed to effectively assist in hip flexion-extension during locomotion with a minimum impact on the physiological human kinematics, owing to a set of passive degrees of freedom for self-alignment of the human and robotic hip flexion-extension axes. Five healthy volunteers walked on a treadmill at different speeds without and with the APO under different levels of assistance. The user-APO physical interaction was evaluated in terms of: (i) the deviation of human lower-limb joint kinematics when wearing the APO with respect to the physiological behavior (i.e., without the APO); (ii) relative displacements between the APO orthotic shells and the corresponding body segments; and (iii) the discrepancy between the kinematics of the APO and the wearer’s hip joints. The results show: (i) negligible interference of the APO in human kinematics under all the experimented conditions; (ii) small (i.e., < 1 cm) relative displacements between the APO cuffs and the corresponding body segments (called stability); and (iii) significant increment in the human-robot kinematics discrepancy at the hip flexion-extension joint associated with speed and assistance level increase. APO mechanics and actuation have negligible interference in human locomotion. Human kinematics was not affected by the APO under all tested conditions. In addition, under all tested conditions, there was no relevant relative displacement between the orthotic cuffs and the corresponding anatomical segments. Hence, the physical human-robot coupling is reliable. These facts prove that the adopted mechanical design of passive degrees of freedom allows an effective human-robot kinematic coupling. We believe that this analysis may be useful for the definition of evaluation metrics for the ergonomics assessment of wearable robots.