by Keyword: Wearables
Blanco-Almazan, Dolores, Groenendaal, Willemijn, Lijnen, Lien, Onder, Rana, Smeets, Christophe, Ruttens, David, Catthoor, Francky, Jane, Raimon, (2022). Breathing Pattern Estimation Using Wearable Bioimpedance for Assessing COPD Severity Ieee Journal Of Biomedical And Health Informatics 26, 5983-5991
JTD Keywords: 6mwt, activation, breathing pattern, burden, chronic obstructive pulmonary disease, exercise, muscles, pressure, pulmonary, signals, variability, volumes, wearables, Bioimpedance, Impedance pneumography
Romero, Daniel, Blanco-Almazán, Dolores, Groenendaal, Willemijn, Lijnen, Lien, Smeets, Christophe, Ruttens, David, Catthoor, Francky, Jané, Raimon, (2022). Predicting 6-minute walking test outcomes in patients with chronic obstructive pulmonary disease without physical performance measures Computer Methods And Programs In Biomedicine 225, 107020
JTD Keywords: bayesian networks, copd, distance, exercise capacity, physical capacity, reference equations, severity, survival, wearables, 6mwt, Heart-rate recovery
Mura, A, Maier, M, Ballester, BR, Costa, JD, Lopez-Luque, J, Gelineau, A, Mandigout, S, Ghatan, PH, Fiorillo, R, Antenucci, F, Coolen, T, Chivite, I, Callen, A, Landais, H, Gomez, OI, Melero, C, Brandi, S, Domenech, M, Daviet, JC, Zucca, R, Verschure, PFMJ, (2022). Bringing rehabilitation home with an e-health platform to treat stroke patients: study protocol of a randomized clinical trial (RGS@home) Trials 23, 518
Background: There is a pressing need for scalable healthcare solutions and a shift in the rehabilitation paradigm from hospitals to homes to tackle the increase in stroke incidence while reducing the practical and economic burden for patients, hospitals, and society. Digital health technologies can contribute to addressing this challenge; however, little is known about their effectiveness in at-home settings. In response, we have designed the RGS@home study to investigate the effectiveness, acceptance, and cost of a deep tech solution called the Rehabilitation Gaming System (RGS). RGS is a cloud-based system for delivering Al-enhanced rehabilitation using virtual reality, motion capture, and wearables that can be used in the hospital and at home. The core principles of the brain theory-based RGS intervention are to deliver rehabilitation exercises in the form of embodied, goal-oriented, and task-specific action.; Methods: The RGS@home study is a randomized longitudinal clinical trial designed to assess whether the combination of the RGS intervention with standard care is superior to standard care alone for the functional recovery of stroke patients at the hospital and at home. The study is conducted in collaboration with hospitals in Spain, Sweden, and France and includes inpatients and outpatients at subacute and chronic stages post-stroke. The intervention duration is 3 months with assessment at baseline and after 3, 6, and 12 months. The impact of RGS is evaluated in terms of quality of life measurements, usability, and acceptance using standardized clinical scales, together with health economic analysis. So far, one-third of the patients expected to participate in the study have been recruited (N = 90, mean age 60, days after stroke >= 30 days). The trial will end in July 2023.; Discussion: We predict an improvement in the patients' recovery, high acceptance, and reduced costs due to a soft landing from the clinic to home rehabilitation. In addition, the data provided will allow us to assess whether the prescription of therapy at home can counteract deterioration and improve quality of life while also identifying new standards for online and remote assessment, diagnostics, and intervention across European hospitals.
JTD Keywords: Deep tech, E-health, Functional recovery, Home treatment, Motor recovery, Randomized clinical trial, Stroke, Upper extremities, Virtual reality, Wearables
Blanco-Almazan D, Groenendaal W, Lozano-Garcia M, Estrada-Petrocelli L, Lijnen L, Smeets C, Ruttens D, Catthoor F, Jane R, (2021). Combining Bioimpedance and Myographic Signals for the Assessment of COPD during Loaded Breathing Ieee Transactions On Biomedical Engineering 68, 298-307
© 1964-2012 IEEE. Chronic Obstructive Pulmonary Disease (COPD) is one of the most common chronic conditions. The current assessment of COPD requires a maximal maneuver during a spirometry test to quantify airflow limitations of patients. Other less invasive measurements such as thoracic bioimpedance and myographic signals have been studied as an alternative to classical methods as they provide information about respiration. Particularly, strong correlations have been shown between thoracic bioimpedance and respiratory volume. The main objective of this study is to investigate bioimpedance and its combination with myographic parameters in COPD patients to assess the applicability in respiratory disease monitoring. We measured bioimpedance, surface electromyography and surface mechanomyography in forty-three COPD patients during an incremental inspiratory threshold loading protocol. We introduced two novel features that can be used to assess COPD condition derived from the variation of bioimpedance and the electrical and mechanical activity during each respiratory cycle. These features demonstrate significant differences between mild and severe patients, indicating a lower inspiratory contribution of the inspiratory muscles to global respiratory ventilation in the severest COPD patients. In conclusion, the combination of bioimpedance and myographic signals provides useful indices to noninvasively assess the breathing of COPD patients.
JTD Keywords: Bioimpedance, Chronic obstructive pulmonary disease, Inspiratory threshold protocol, Myographic signals, Wearables
De la Torre Costa J, Ballester BR, Verschure PFMJ, (2021). A Rehabilitation Wearable Device to Overcome Post-stroke Learned Non-use. Methodology, Design and Usability Communications In Computer And Information Science 1538 CCIS, 198-205
After a stroke, a great number of patients experience persistent motor impairments such as hemiparesis or weakness in one entire side of the body. As a result, the lack of use of the paretic limb might be one of the main contributors to functional loss after clinical discharge. We aim to reverse this cycle by promoting the use of the paretic limb during activities of daily living (ADLs). To do so, we describe the key components of a system composed of a wearable bracelet (i.e., a smartwatch) and a mobile phone, designed to bring a set of neurorehabilitation principles that promote acquisition, retention and generalization of skills to the home of the patient. A fundamental question is whether the loss in motor function derived from learned–non–use may emerge as a consequence of decision–making processes for motor optimization. Our system is based on well-established rehabilitation strategies that aim to reverse this behaviour by increasing the reward associated with action execution and implicitly reducing the expected cost of using the paretic limb, following the notion of reinforcement–induced movement therapy (RIMT). Here we validate an accelerometer-based measure of arm use and its capacity to discriminate different activities that require increasing movement of the arm. The usability and acceptance of the device as a rehabilitation tool is tested using a battery of self–reported and objective measurements obtained from acute/subacute patients and healthy controls. We believe that an extension of these technologies will allow for the deployment of unsupervised rehabilitation paradigms during and beyond hospitalization time. © 2021, Springer Nature Switzerland AG.
JTD Keywords: adls, hemiparesis, learned non-use, wearables, Activities of daily living, Adls, Functional loss, Generalisation, Hemiparesis, Learned non-use, Motor impairments, Neurorehabilitation , Patient experiences, Stroke, Wearable devices, Wearable technology, Wearables