Beringbartlett9388

Freezing of gait (FOG) is a major hindrance to daily mobility and can lead to falling in people with Parkinson's disease. While wearable accelerometers and gyroscopes have been commonly used for FOG detection, foot plantar pressure distribution could also be considered for this application, given its usefulness in previous gait-based classification. This research examined 325 plantar-pressure based features and 132 acceleration-based features extracted from the walking data of five males with Parkinson's disease who experienced FOG. A set of 61 features calculated from the time domain, Fast Fourier transform (FFT), and wavelet transform (WT) were extracted from multiple input signals; including, total ground reaction force, foot centre of pressure (COP) position, COP velocity, COP acceleration, and 3D ankle acceleration. SBFI26 Minimum-redundancy maximum relevance (mRMR) feature selection was used to rank all features. Plantar-pressure based features accounted for 4 of the top 5 features (ranks 2, 3, 4, 5); the remaining feature was an ankle acceleration based feature (rank 1). The three highest ranked features were the freeze index (calculated from ankle acceleration), total power in the frequency domain (calculated using the FFT from COP velocity), and mean of the WT detail coefficients (calculated from COP velocity). This preliminary analysis demonstrated that features calculated from plantar pressure, specifically COP velocity, performed comparably to ankle acceleration features. Thus, feature sets for FOG detection may benefit from plantar-pressure based features.Spine Curvature Disorder (SCD) is a medical condition that affects the shape of the spine. Methods of monitoring SCDs involve visual inspection followed by X-rays and measurements. Once a patient is diagnosed with SCD and treatment or therapy is implemented, progress is tracked by exposing the patient to multiple periodic X-rays to determine the spine responses to treatments or therapies. Multiple exposures to X-rays is not desirable and is also costly. Therefore, we propose a new method for detecting and monitoring SCD and present our initial research results. We are implementing a non-invasive method that can detect and monitor the spinal postures of SCD. Magnets are placed on a shirt a grid form then a sensor system would be placed on the chest of the body. An on-body magnetic sensor records the sensor data values to determine if the upper body posture is straight or is curved which in turn can assist in detecting if the spine is deformed. We present our initial results on magnetic sensor testing and preliminary results using wearable sensors and a garment integrated magnetic shirt.This paper presents a novel method for tracking gaiting-based (changing contacts, reciprocal, cyclical) withinhand manipulation strategies of a human hand. We present a kinematic model that relies on data collected from 6-DOF magnetic sensors attached to 7 external sites on the hand. The sensors are calibrated by three procedures-sensor-to-fingertip, constrained fingertip workspace limits, and flat hand configuration. Subjects rotated two cubes of different sizes around the 3 object-centric axes, while a synchronized camera recorded the object motion. Hand motions were segmented and then averaged using dynamic time warping (DTW) to yield a representative time-series motion primitive for the given task. The hand movements of two subjects during cube rotation tasks were reconstructed using a 22-degree of freedom (DOF) hand kinematic model. Based on a qualitative evaluation of the joint movements, intrasubject correlations of joint angles were found.Reach-to-grasp actions have been recently studied to highlight how intentions influence action planning and shapes the movement kinematics. Reach-to-grasp (RG) kinematics can reveal important information on motor planning and control in several pathologies, including neurodegenerative diseases. Current methods are mainly based on optoelectronic analysis systems, which provide accurate movement tracking but are expensive, time-consuming, and limited to constrained research-oriented space. In this study, we proposed an innovative, non-invasive, and easy-to-use ringshaped wearable system, named SensRing, able to record inertial data during the movement. To ensure accurate and precise measures, which are mandatory for clinical practice, a preliminary technical validation of the SensRing with respect to the Vicon (i.e., gold standard for motion analysis) was performed on two finger tapping exercises. Preliminary results pointed out very low discrepancies in terms of absolute errors (AbsErr) between the values of repetitions (AbsErr≤0.8), frequency (AbsErr=0.04Hz) and amplitude (AbsErr≤2.7deg) measured by the two systems, as well as high correlation between the measures obtained with the inertial and optical system. Therefore, inertial data from the SensRing were used in a "reach-to-grasp and move" protocol to calculate the performance of a group of healthy young subjects during three RG and move sequences. Particularly, subjects were instructed to reach and grasp a bottle to drink (DRINK), to place it on the table (IND) or to pass it to another partner (SOC). Results showed that SensRing could identify that, in the RG phase, different intentions determine different kinematic parameters of grasping the same object. As concerns the phase of moving, if the movement is different (drink vs IND/SOC) it's easier to find differences between the tasks, but also when the action is the same but with different social intent (IND vs SOC) SensRing found a significant difference.Intravenous needle insertion is typically conducted manually, with needles guided into vessels by feel while looking for a brief flash of blood. This process is imprecise and leads to mispositioned needles, multiple reinsertion attempts, increased procedure time and higher costs for the hospital. We present a method for indicating that the needle has reached the vein by measuring the change in mechanical impedance of the needle as it passes through different tissue layers. Testing in a phantom indicated that this has the potential to identify transitions through tissue boundaries.