Exoskeletons are mechatronic systems worn by a person in such a way that the physical interface permits a direct transfer of mechanical power and exchange of information. Upper limb robotic exoskeletons may be helpful for people with disabilities and/or limb weakness or injury. Tremor is the most common movement disorder in neurological practice. In addition to medication, rehabilitation programs, and deep brain stimulation, biomechanical loading has appeared as a potential tremor suppression alternative. This paper introduces the robotic exoskeleton called WOTAS (wearable orthosis for tremor assessment and suppression) that provides a means of testing and validating nongrounded control strategies for orthotic tremor suppression. This paper describes in detail the general concept for WOTAS, outlining the special features of the design and selection of system components. Two control strategies developed for tremor suppression with exoskeletons are described. These two strategies are based on biomechanical loading and notch Altering the tremor through the application of internal forces. Results from experiments using these two strategies on patients with tremor are summarized. Finally, results from clinical trials are presented, which indicate the feasibility of ambulatory mechanical

This paper presents a novel calibration procedure as a simple, yet powerful, method to place and align inertial sensors with body segments. The calibration can be easily replicated without the need of any additional tools. The proposed method is validated in three different applications: a computer mathematical simulation; a simplified joint composed of two semi-spheres interconnected by a universal goniometer; and a real gait test with five able-bodied subjects. Simulation results demonstrate that, after the calibration method is applied, the joint angles are correctly measured independently of previous sensor placement on the joint, thus validating the proposed procedure. In the cases of a simplified joint and a real gait test with human volunteers, the method also performs correctly, although secondary plane errors appear when compared with the simulation results. We believe that such errors are caused by limitations of the current inertial measurement unit (IMU) technology and fusion algorithms. In conclusion, the presented calibration procedure is an interesting option to solve the alignment problem when using IMUs for gait analysis.

Tremor is one of the most prevalent movement disorders. There is a large proportion of patients (around 25%) in whom current treatments do not attain a significant tremor reduction. This paper proposes a tremor suppression strategy that detects tremor from the electromyographic signals of the muscles from which tremor originates and counteracts it by delivering electrical stimulation to the antagonist muscles in an out of phase manner. The detection was based on the iterative Hilbert transform and stimulation was delivered above the motor threshold (motor stimulation) and below the motor threshold (sensory stimulation). The system was tested on six patients with predominant wrist flexion/extension tremor (four with Parkinson disease and two with Essential tremor) and led to an average tremor reduction in the range of 46%-81% and 35%-48% across five patients when using the motor and sensory stimulation, respectively. In one patient, the system did not attenuate tremor. These results demonstrate that tremor attenuation might be achieved by delivering electrical stimulation below the motor threshold, preventing muscle fatigue and discomfort for the patients, which sets the basis for the development of an alternative treatment for tremor.

The advances and fast spread of mobile devices and technologies, we witness today, have extended its advantages over medical and health practice supported by mobile devices, giving rise to the growing research of Internet of Things (IoT), especially the e-Health field. The features provided by mobile technologies revealed to be of major importance when we consider the continuous aging of population and the consequent increase of its debilities. In addition to the increase of lifetime span of population, also the increase of health risks and their locomotive impairments increases, requiring a close monitoring and continuous evaluation. Such monitoring should be as noninvasive as possible, in order not to compromise the mobility and the day-to-day activities of citizens. Therefore, we present the development of a noninvasive optical fiber sensor (OFS) architecture adaptable to a shoe sole for plantar pressure remote monitoring, which is suitable to be integrated in an IoT e-Health solution to monitor the well-being of individuals. This paper explores the production of the OFS multiplexed network (using fiber Bragg gratings) to monitor the foot plantar pressure distribution during gait (walking movement). From the acquired gait data, it is possible to infer health conditions of the patient's foot and spine posture. To guarantee the patients mobility, the proposed system consists of an OFS network integrated with a wireless transceiver to enable efficient ubiquitous monitoring of patients. This paper shows the calibration and measurement results, which reflect the accuracy of the proposed system, under normal walking in controlled area.

This paper presents a two stage algorithm for real-time estimation of instantaneous tremor parameters from gyroscope recordings. Gyroscopes possess the advantage of providing directly joint rotational speed, overcoming the limitations of traditional tremor recording based on accelerometers. The proposed algorithm first extracts tremor patterns from raw angular data, and afterwards estimates its instantaneous amplitude and frequency. Real-time separation of voluntary and tremorous motion relies on their different frequency contents, whereas tremor modelling is based on an adaptive LMS algorithm and a Kalman filter. Tremor parameters will be employed to drive a neuroprosthesis for tremor suppression based on biomechanical loading.