Effect of a Soft Robotic Sock Device on Lower Extremity Rehabilitation Following Stroke: A Preliminary Clinical Study With Focus on Deep Vein Thrombosis Prevention

Developing and Validating a New Model to Predict the Risk of Poor Neurological Status of Acute Ischemic Stroke After Intravenous Thrombolysis

OBJECTIVES

The objective of this study was to develop and validate a predictive model for the risk of poor neurological status in in-hospital patients with acute ischemic stroke (AIS) after intravenous thrombolysis.

METHODS

This 2-center retrospective study included patients with AIS treated at the Advanced Stroke Center of the Second Hospital of Hebei Medical University and Baoding No.1 Central Hospital between January 2018 and January 2020). The neurological function status at day 7 of AIS onset was used as the endpoint of the study, which was evaluated using the National Institute of Health Stroke Scale (NIHSS) score.

RESULTS

A total of 878 patients were included in the study and divided into training (n=652) and validation (n=226) sets. Seven variables were selected as predictors to establish the risk model: age, NIHSS before thrombolysis (NIHSS1), NIHSS 24 hours after thrombolysis (NIHSS3), high-density lipoprotein, antiplatelet, cerebral computed tomography after thrombolysis (CT2), and lower extremity venous color Doppler ultrasound. The risk prediction model achieved good discrimination (the areas under the Receiver Operating Characteristic curve in the training and validation sets were 0.9626 and 0.9413, respectively) and calibration (in the training set Emax=0.072, Eavg=0.01, P =0.528, and in the validation set Emax=0.123, Eavg=0.019, P =0.594, respectively). The decision curve analysis showed that the model could achieve a good net benefit.

CONCLUSIONS

The prediction model obtained in this study showed good discrimination, calibration, and clinical efficacy. This new nomogram can provide a reference for predicting the risk of poor neurological status in patients with acute ischemic stroke after intravenous thrombolysis.

Perturbation-Based Balance Exercise Using a Wearable Device to Improve Reactive Postural Control

Reactive postural control is an important component of the balance function for fall prevention. Perturbation-based balance exercises improve reactive postural control; however, these exercises require large, complex instruments and expert medical guidance. This study investigates the effects of unexpected perturbation-based balance exercises using a wearable balance exercise device (WBED) on reactive postural control. Eighteen healthy adult males participated in this study. Participants were assigned to the WBED and Sham groups. In the intervention session, participants in the WBED group randomly underwent unexpected perturbation in the mediolateral direction, while the Sham group performed the same exercises without perturbation. Before and after the intervention session, all participants underwent evaluation of reactive balance function using air cylinders. Peak displacement (D), time at peak displacement (T), peak velocity (V), and root mean square (RMS) of center of pressure (COP) data were measured. For mediolateral and anteroposterior COP (COPML and COP[Formula: see text]), the main effects of group and time factors (pre/post) were investigated through the analysis of variance for split-plot factorial design. In the WBED group, the D-COPML and V-COPML of the post-test significantly decreased compared to those of the pre-test (p = 0.017 and p = 0.003, respectively). Furthermore, the D-COPAP and RMSAP of the post-test significantly decreased compared to those of the pre-test (p = 0.036 and p = 0.015, respectively). This study proved that the perturbation-based balance exercise using WBED immediately improved reactive postural control. Therefore, wearable exercise devices, such as WBED, may contribute to the prevention of falls and fall-related injuries.

Smart Health-Enhanced Early Mobilisation in Intensive Care Units

Critically ill patients that stay in Intensive Care Units (ICU) for long periods suffer from Post-Intensive Care Syndrome or ICU Acquired Weakness, whose effects can decrease patients' quality of life for years. To prevent such issues and aiming at shortening intensive care treatments, Early Mobilisation (EM) has been proposed as an encouraging technique: the literature includes numerous examples of the benefits of EM on the prevention of post-operative complications and adverse events. However, the appropriate application of EM programmes entails the use of scarce resources, both human and technical. Information and Communication Technologies can play a key role in reducing cost and improving the practice of EM. Although there is rich literature on EM practice and its potential benefits, there are some barriers that must be overcome, and technology, i.e., the use of sensors, robotics or information systems, can contribute to that end. This article reviews the literature and analyses on the use of technology in the area of EM, and moreover, it proposes a smart health-enhanced scenario.

Robotic Home-Based Rehabilitation Systems Design: From a Literature Review to a Conceptual Framework for Community-Based Remote Therapy During COVID-19 Pandemic

During the COVID-19 pandemic, the higher susceptibility of post-stroke patients to infection calls for extra safety precautions. Despite the imposed restrictions, early neurorehabilitation cannot be postponed due to its paramount importance for improving motor and functional recovery chances. Utilizing accessible state-of-the-art technologies, home-based rehabilitation devices are proposed as a sustainable solution in the current crisis. In this paper, a comprehensive review on developed home-based rehabilitation technologies of the last 10 years (2011-2020), categorizing them into upper and lower limb devices and considering both commercialized and state-of-the-art realms. Mechatronic, control, and software aspects of the system are discussed to provide a classified roadmap for home-based systems development. Subsequently, a conceptual framework on the development of smart and intelligent community-based home rehabilitation systems based on novel mechatronic technologies is proposed. In this framework, each rehabilitation device acts as an agent in the network, using the internet of things (IoT) technologies, which facilitates learning from the recorded data of the other agents, as well as the tele-supervision of the treatment by an expert. The presented design paradigm based on the above-mentioned leading technologies could lead to the development of promising home rehabilitation systems, which encourage stroke survivors to engage in under-supervised or unsupervised therapeutic activities.

Wireless Ti3C2Tx MXene Strain Sensor with Ultrahigh Sensitivity and Designated Working Windows for Soft Exoskeletons

Emerging soft exoskeletons pose urgent needs for high-performance strain sensors with tunable linear working windows to achieve a high-precision control loop. Still, the state-of-the-art strain sensors require further advances to simultaneously satisfy multiple sensing parameters, including high sensitivity, reliable linearity, and tunable strain ranges. Besides, a wireless sensing system is highly desired to enable facile monitoring of soft exoskeleton in real time, but is rarely investigated. Herein, wireless Ti₃C₂T_x MXene strain sensing systems were fabricated by developing hierarchical morphologies on piezoresistive layers and incorporating regulatory resistors into circuit designs as well as integrating the sensing circuit with near-field communication (NFC) technology. The wireless MXene sensor system can simultaneously achieve an ultrahigh sensitivity (gauge factor ≥ 14,000) and reliable linearity (R² ≈ 0.99) within multiple user-designated high-strain working windows (130% to ≥900%). Additionally, the wireless sensing system can collectively monitor the multisegment exoskeleton actuations through a single database channel, largely reducing the data processing loading. We finally integrate the wireless, battery-free MXene e-skin with various soft exoskeletons to monitor the complex actuations that assist hand/leg rehabilitation.