Detection and classification of multidirectional steps for motor-cognitive training in older adults using shoe-mounted inertial sensors.

Interactive games have the potential to mitigate or prevent gait impairments and cognitive decline in older adults. This study aimed at developing a novel real-time step detection and direction classification approach to be used in the evaluation of multidirectional steps and interaction while playing motor-cognitive games. Two shoe-mounted inertial sensors were used to capture foot motions, which were treated interchangeably after the application of a novel foot sagittal reflection method. A single multi-class classifier was able to distinguish step direction with an accuracy of 98.1%. Experimental results support the applicability of the solution in the context of interactive motor-cognitive training.

Calibration and Electrical Validation of a BIS Portable System.

Heart failure (HF) affects at least 26 million people worldwide and is considered a global pandemic. Almost 1 out of 4 hospitalised patients are re-hospitalised for HF within the 30-day post-discharge period. This can be avoided if changes to the hemodynamics of the HF patient's body are early detected. Bioimpedance Spectroscopy (BIS) is a method that allows the measurement and analysis of multi-frequency body complex impedance and can be used to detect changes to the HF patient's hemodynamics. This paper presents the calibration and validation process of a low-cost portable BIS system, as well as, the study of the best Cole parameter estimation methods. The BIS system was calibrated using a three reference circuit method and a Resistance-Capacitance-Inductance (RCL) meter as calibration system. After calibration, BIS impedance measurements of validation circuits presented an average phase error of 0.76 degrees and an average magnitude relative error of 0.6% when compared with standard values. Regarding Cole parameters estimation, using the Impedance model and the Non-Linear Least Squares method for curve fitting, the relative errors were below 4% when compared with the expected values.

Classification of knee arthropathy with accelerometer-based vibroarthrography.

One of the most common knee joint disorders is known as osteoarthritis which results from the progressive degeneration of cartilage and subchondral bone over time, affecting essentially elderly adults. Current evaluation techniques are either complex, expensive, invasive or simply fails into detection of small and progressive changes that occur within the knee. Vibroarthrography appeared as a new solution where the mechanical vibratory signals arising from the knee are recorded recurring only to an accelerometer and posteriorly analyzed enabling the differentiation between a healthy and an arthritic joint. In this study, a vibration-based classification system was created using a dataset with 92 healthy and 120 arthritic segments of knee joint signals collected from 19 healthy and 20 arthritic volunteers, evaluated with k-nearest neighbors and support vector machine classifiers. The best classification was obtained using the k-nearest neighbors classifier with only 6 time-frequency features with an overall accuracy of 89.8% and with a precision, recall and f-measure of 88.3%, 92.4% and 90.1%, respectively. Preliminary results showed that vibroarthrography can be a promising, non-invasive and low cost tool that could be used for screening purposes. Despite this encouraging results, several upgrades in the data collection process and analysis can be further implemented.

Low-cost wearable data acquisition for stroke rehabilitation: a proof-of-concept study on accelerometry for functional task assessment.

BACKGROUND: An increasingly aging society and consequently rising number of patients with poststroke-related neurological dysfunctions are forcing the rehabilitation field to adapt to ever-growing demands. Although clinical reasoning within rehabilitation is dependent on patient movement performance analysis, current strategies for monitoring rehabilitation progress are based on subjective time-consuming assessment scales, not often applied. Therefore, a need exists for efficient nonsubjective monitoring methods. Wearable monitoring devices are rapidly becoming a recognized option in rehabilitation for quantitative measures. Developments in sensors, embedded technology, and smart textile are driving rehabilitation to adopt an objective, seamless, efficient, and cost-effective delivery system. This study aims to assist physiotherapists' clinical reasoning process through the incorporation of accelerometers as part of an electronic data acquisition system. METHODS: A simple, low-cost, wearable device for poststroke rehabilitation progress monitoring was developed based on commercially available inertial sensors. Accelerometry data acquisition was performed for 4 first-time poststroke patients during a reach-press-return task. RESULTS: Preliminary studies revealed acceleration profiles of stroke patients through which it is possible to quantitatively assess the functional movement, identify compensatory strategies, and help define proper movement. CONCLUSION: An inertial data acquisition system was designed and developed as a low-cost option for monitoring rehabilitation. The device seeks to ease the data-gathering process by physiotherapists to complement current practices with accelerometry profiles and aid the development of quantifiable methodologies and protocols.

Anticipatory postural adjustments during sitting reach movement in post-stroke subjects.

The study assessed the effect of velocity of arm movement on anticipatory postural adjustments (APAs) generation in the contralateral and ipsilateral muscles of individuals with stroke in seating. Ten healthy and eight post-stroke subjects were studied in sitting. The task consisted in reaching an object placed at scapular plane and mid-sternum height at self-selected and fast velocities. Electromyography was recorded from anterior deltoid (AD), upper (UT) and lower trapezius (LT) and latissimus dorsi (LD). While kinematic analysis was used to assess peak velocity and trunk displacement. Differences were found between the timing of APAs on ipsi and contralateral LD and LT in both movement speeds and in ipsilateral UT during movement of the non-affected arm at a self-selected velocity. A delay on the contralateral LD to reach movement with the non-affected arm at fast velocity was also observed. The trunk displacement was greater in post-stroke subjects. Individuals with stroke demonstrated a delay of APAs in the muscles on both sides of the body compared to healthy subjects. The delay was observed during performance of the reaching task with the fast and self-selected velocity.

Active illumination single-pixel camera based on compressive sensing.

We present an optical imaging system based on compressive sensing (CS) along with its principal mathematical aspects. Although CS is undergoing significant advances and empowering many discussions and applications throughout various fields, this article focuses on the analysis of a single-pixel camera. This work was the core for the development of a single-pixel camera approach based on active illumination. Therefore, the active illumination concept is described along with the experimental results, which were very encouraging toward the development of compressive-sensing-based cameras for various applications, such as pixel-level programmable gain imaging.