![]() ![]() Furthermore, there is no accepted model to separate gravity from voluntary motion in the accelerometer data (Veltink et al., 1996 Sabatini, 2011). They however measure linear acceleration, in contrast to human motion which is considered as rotations about joints. Accelerometers constitute the most popular approach. ( 2013) implemented microelectromechanical (MEMS) gyroscopes for measuring tremor. For example, the neuroprosthesis presented in Gallego et al. Both MEMS accelerometers and gyroscopes are used to monitor tremor (Grimaldi et al., 2008 Elble, 2009). Unlike wearable robots, where most sensors are embedded in the device, neuroprostheses depend on additional sensors. Tremor suppression devices subsequently intervene only when tremor coincides with voluntary movement. This is typically performed using adaptive algorithms (see e.g., Gallego et al., 2010 Bo et al., 2011). To avoid constant actuation and the reduction of tremor without functional improvement, total movement must be separated into voluntary and tremulous movement (Rocon et al., 2007a). Functional electrical stimulation neuroprostheses avoid a heavier and more obtrusive rigid structure (Gallego et al., 2011). Other studies have shown that it is possible to attenuate the tremor using the human muscle tissue as actuators, through functional electrical stimulation (Javidan et al., 1992 Popović Maneski et al., 2011 Gallego et al., 2013 Bó et al., 2014). demonstrated for the first time that a wearable robot that applied force to the upper limb segments could effectively attenuate upper limb tremors (Rocon et al., 2007a). Tremor suppression through mechanical loading is based on the principle that tremor amplitude can be modified by altering limb impedance through the application of force or by adding mass (Adelstein, 1981 Prochazka et al., 1992 Rocon et al., 2007a). These novel strategies are deemed necessary given the low success rate and side effects induced by both drugs and neurosurgery in some types of patients in 25% of patients tremor is not managed satisfactorily (Rocon et al., 2007b). Recently new tremor treatment strategies, based on mechanical loading, have been proposed in addition to the existing therapies. In this article we refer to pathological tremor as tremor. Furthermore, patients suffering from pathological tremor experience functional disability to the extent that it can lead to social isolation. Sixty five percent (Elble and Koller, 1990) of tremor patients report serious difficulties in the performance of their activities of daily living (ADL) (McAuley, 2000 E Rocon, 2004 Wenning et al., 2005). Pathological tremor encompasses all types of tremors that impair motor performance (e.g., essential tremor and parkinsonian tremor McAuley and Marsden, 2000), and is the most common movement disorder (Wenning et al., 2005). The methods presented in this study constitute an important step toward more user-friendly and context-aware neuroprostheses for tremor suppression and monitoring. Kinematic tracking error values with an average deviation of 8% demonstrate our ability to estimate tremor from orientation data. Relative sensor location was detected with an accuracy of 94.12% for the 4 MIMU configuration, and 100% for the 3 MIMU configurations. Subsequently we demonstrate how tremor parameters can be extracted from orientation data using an adaptive estimation algorithm. We focus on relative rather than absolute sensor location, because in many medical applications magnetic and inertial measurement units (MIMU) are used in a chain stretching over adjacent segments, or are always placed on a fixed set of locations. First, we describe a novel relative sensor placement identification technique based on orientation data. In this paper we present two algorithms that enable the robust extraction of joint angle and related features to enable long-term continuous monitoring of tremor with context awareness. Traditionally kinematic features are used to extract context information, with most recently the use of joint angles as highly potential features. Context awareness is a major challenge for neuroprostheses and would allow these devices to react more quickly and appropriately to the changing demands of the user and/or task. To enrich the interpretation of data recorded during long-term tremor monitoring and to increase the intelligence of tremor suppression neuroprostheses we need to be aware of the context. Neuroprostheses that stimulate the sensorimotor pathways are one of the most promising alternatives although they are still under development. Upper limb tremor is the most prevalent movement disorder and, unfortunately, it is not effectively managed in a large proportion of the patients. ![]()
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