Brain–machine interfaces (BMIs) are promising devices that can be used as neuroprostheses by severely disabled individuals. Brain surface electroencephalograms (electrocorticograms, ECoGs) can provide input signals that can then be decoded to enable communication with others and to control intelligent prostheses and home electronics. However, conventional systems use wired ECoG recordings. Therefore, the development of wireless systems for clinical ECoG BMIs is a major goal in the field. We developed a fully implantable ECoG signal recording device for human ECoG BMI, i.e., a wireless human ECoG-based real-time BMI system (W-HERBS). In this system, three-dimensional (3D) high-density subdural multiple electrodes are fitted to the brain surface and ECoG measurement units record 128-channel (ch) ECoG signals at a sampling rate of 1 kHz. The units transfer data to the data and power management unit implanted subcutaneously in the abdomen through a subcutaneous stretchable spiral cable. The data and power management unit then communicates with a workstation outside the body and wirelessly receives 400 mW of power from an external wireless transmitter. The workstation records and analyzes the received data in the frequency domain and controls external devices based on analyses. We investigated the performance of the proposed system. We were able to use W-HERBS to detect sine waves with a 4.8-μV amplitude and a 60–200-Hz bandwidth from the ECoG BMIs. W-HERBS is the first fully implantable ECoG-based BMI system with more than 100 ch. It is capable of recording 128-ch subdural ECoG signals with sufficient input-referred noise (3 μVrms) and with an acceptable time delay (250 ms). The system contributes to the clinical application of high-performance BMIs and to experimental brain research.

The aim of this study was to obtain quantitative results about shoulder contact force during wheelchair lever propulsion when the gear ratio of the lever propulsion mechanism is changing. The effect of the gear ratio on the shoulder contact force was investigated for few different wheelchair loading. For the experiments we designed a special mechatronic wheelchair simulator that allowed the simulation of different gear ratios of the wheelchair lever propulsion mechanism and simulation of different road inclinations. The same simulator was also used for simulation of a hand rim propelled wheelchair. We conducted also a handrim propulsion experiment and used the results from it for comparison with the lever propulsion data. Four nondisabled male adults with no prior wheeling experience participated in the experiment. In the first tests, a lever propelled wheelchair was simulated with the simulator. The target speed of the wheelchair was set to 2 km/h. For the test, the gear ratio was varied from 1.5 to 1/1.5. A load torque was applied to the rear wheels to imitate road inclinations of 0°, 2° and 4°. In the second part of the test, the simulator was structured to simulate a handrim propelled wheelchair. The participants were asked to keep the same speed (2 km/h) and the simulator was set sequentially to imitate climbing a ramp inclined on 0°, 2° and 4°. Kinematic data of the body were collected by a motion capture system. Kinetic data such as hand force and driving torque, were measured by instrumented wheels with incorporated six-axis force sensor. The intersegmental joint forces and moments were calculated from the obtained kinematic and kinetic data via inverse dynamics analysis procedure. Muscle forces were computed from the measured joint moments by using an optimization approach. Shoulder joint contact force, which indicates the joint surface loading, was computed as a synthetic vector of the intersegmental force for shoulder joint acquired from the inverse dynamics analysis and the compressive forces from muscles, tendons, ligaments and cartilages crossing the shoulder joint. It was observed that the decrease of the gear ratio causes increased cycle frequency and reduces the shoulder joint contact force. Result showed that the shoulder joint contact force during lever propulsion with a gear ratio 1/1.5 was up to 70 % lower than the shoulder joint contact force during handrim propulsion. The results from this study could be used in the design of new lever propulsion mechanisms that reduce the risks of secondary shoulder disorders and increase user's comfort.

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Wheelchair efficiency depends significantly on the individual adjustment of the wheelchair propulsion interface. Wheelchair prescription involves reconfiguring the wheelchair to optimize it for specific user characteristics. Wheelchair tuning procedure is a complicated task that is performed usually by experienced rehabilitation engineers. In this study, we report initial results from the development of a musculoskeletal model of the wheelchair lever propulsion. Such a model could be used for the development of new advanced wheelchair approaches that allow wheelchair designers and practitioners to explore virtually, on a computer, the effects of the intended settings of the lever-propulsion interface. To investigate the lever-propulsion process, we carried out wheelchair lever propulsion experiments where joint angle, lever angle and three-directional forces and moments applied to the lever were recorded during the execution of defined propulsion motions. Kinematic and dynamic features of lever propulsion motions were extracted from the recorded data to be used for the model development. Five healthy male adults took part in these initial experiments. The analysis of the collected kinematic and dynamic motion parameters showed that lever propulsion is realized by a cyclical three-dimensional motion of upper extremities and that joint torque for propulsion is maintained within a certain range. The synthesized propulsion model was verified by computer simulation where the measured lever-angles were compared with the angles generated by the developed model simulation. Joint torque amplitudes were used to impose the torque limitation to the model joints. The results evidenced that the developed model can simulate successfully basic lever propulsion tasks such as pushing and pulling the lever.