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Sensing and Signal Processing Technologies for Outpatient Monitoring and Rehabilitation

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: 25 December 2024 | Viewed by 8894

Special Issue Editors

Department of Materials and Production, Aalborg University, Fibigerstraede 16, DK-9220 Aalborg East, Denmark
Interests: biomechanical analysis; sensors; monitoring of outpatients; rehabilitation
Interdisciplinary Orthopaedics, Aalborg University Hospital, 9000 Aalborg, Denmark
Interests: wearable sensors; post-operative care; gait analysis

Special Issue Information

Dear Colleagues,

The ageing society and the growing prevalence of population diseases will stretch hospital capacity to the limits, and the increased use of outpatient solutions seems inevitable. Outpatient solutions have several medical benefits, such as faster rehabilitation and improved quality-of-life for patients, but they also pose technical challenges in terms of disease monitoring and rehabilitation progression as well as the identification of situations that require medical intervention. Most of the conceivable technologies rely on sensors and signal processing to some extent, and the associated science is the focus of this Special Issue. Topics include, but are not limited to:

  • Sensing technologies for disease and rehabilitation monitoring;
  • Wearable and ubiquitous sensing technologies;
  • Model-based technologies for the estimation of disease and rehabilitation progress from sensor signals;
  • Infrastructure solutions for the management of outpatient populations;
  • Sensing technologies for rehabilitation and independence-improving technology such cobots and exoskeletons.

The aforementioned technologies are particularly relevant for population diseases such as diabetes, osteoarthritis and Parkinson’s disease, but they are also important for the management of congenital or progressive conditions such as cerebral palsy, amyotrophic lateral sclerosis and multiple sclerosis.

Prof. Dr. John Rasmussen
Dr. Arash Ghaffari
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sensor data processing
  • wearable biomarkers
  • outpatient monitoring
  • remote patient rehabilitation
  • telemedicine

Published Papers (5 papers)

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Research

10 pages, 481 KiB  
Article
Excessive Oxygen Administration in High-Risk Patients Admitted to Medical and Surgical Wards Monitored by Wireless Pulse Oximeter
by Clara E. Mathar, Camilla Haahr-Raunkjær, Mikkel Elvekjær, Ying Gu, Claire P. Holm, Michael P. Achiam, Lars N. Jorgensen, Eske K. Aasvang and Christian S. Meyhoff
Sensors 2024, 24(4), 1139; https://doi.org/10.3390/s24041139 - 09 Feb 2024
Viewed by 510
Abstract
The monitoring of oxygen therapy when patients are admitted to medical and surgical wards could be important because exposure to excessive oxygen administration (EOA) may have fatal consequences. We aimed to investigate the association between EOA, monitored by wireless pulse oximeter, and nonfatal [...] Read more.
The monitoring of oxygen therapy when patients are admitted to medical and surgical wards could be important because exposure to excessive oxygen administration (EOA) may have fatal consequences. We aimed to investigate the association between EOA, monitored by wireless pulse oximeter, and nonfatal serious adverse events (SAEs) and mortality within 30 days. We included patients in the Capital Region of Copenhagen between 2017 and 2018. Patients were hospitalized due to acute exacerbation of chronic obstructive pulmonary disease (AECOPD) or after major elective abdominal cancer surgery, and all were treated with oxygen supply. Patients were divided into groups by their exposure to EOA: no exposure, exposure for 1–59 min or exposure over 60 min. The primary outcome was SAEs or mortality within 30 days. We retrieved data from 567 patients for a total of 43,833 h, of whom, 63% were not exposed to EOA, 26% had EOA for 1–59 min and 11% had EOA for ≥60 min. Nonfatal SAEs or mortality within 30 days developed in 24%, 12% and 22%, respectively, and the adjusted odds ratio for this was 0.98 (95% CI, 0.96–1.01) for every 10 min. increase in EOA, without any subgroup effects. In conclusion, we did not observe higher frequencies of nonfatal SAEs or mortality within 30 days in patients exposed to excessive oxygen administration. Full article
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17 pages, 3042 KiB  
Article
Multimodality Video Acquisition System for the Assessment of Vital Distress in Children
by Vincent Boivin, Mana Shahriari, Gaspar Faure, Simon Mellul, Edem Donatien Tiassou, Philippe Jouvet and Rita Noumeir
Sensors 2023, 23(11), 5293; https://doi.org/10.3390/s23115293 - 02 Jun 2023
Viewed by 1282
Abstract
In children, vital distress events, particularly respiratory, go unrecognized. To develop a standard model for automated assessment of vital distress in children, we aimed to construct a prospective high-quality video database for critically ill children in a pediatric intensive care unit (PICU) setting. [...] Read more.
In children, vital distress events, particularly respiratory, go unrecognized. To develop a standard model for automated assessment of vital distress in children, we aimed to construct a prospective high-quality video database for critically ill children in a pediatric intensive care unit (PICU) setting. The videos were acquired automatically through a secure web application with an application programming interface (API). The purpose of this article is to describe the data acquisition process from each PICU room to the research electronic database. Using an Azure Kinect DK and a Flir Lepton 3.5 LWIR attached to a Jetson Xavier NX board and the network architecture of our PICU, we have implemented an ongoing high-fidelity prospectively collected video database for research, monitoring, and diagnostic purposes. This infrastructure offers the opportunity to develop algorithms (including computational models) to quantify vital distress in order to evaluate vital distress events. More than 290 RGB, thermographic, and point cloud videos of each 30 s have been recorded in the database. Each recording is linked to the patient’s numerical phenotype, i.e., the electronic medical health record and high-resolution medical database of our research center. The ultimate goal is to develop and validate algorithms to detect vital distress in real time, both for inpatient care and outpatient management. Full article
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15 pages, 2097 KiB  
Article
Accelerations Recorded by Simple Inertial Measurement Units with Low Sampling Frequency Can Differentiate between Individuals with and without Knee Osteoarthritis: Implications for Remote Health Care
by Arash Ghaffari, John Rasmussen, Søren Kold, Rikke Emilie Kildahl Lauritsen, Andreas Kappel and Ole Rahbek
Sensors 2023, 23(5), 2734; https://doi.org/10.3390/s23052734 - 02 Mar 2023
Cited by 1 | Viewed by 1395
Abstract
Determining the presence and severity of knee osteoarthritis (OA) is a valuable application of inertial measurement units (IMUs) in the remote monitoring of patients. This study aimed to employ the Fourier representation of IMU signals to differentiate between individuals with and without knee [...] Read more.
Determining the presence and severity of knee osteoarthritis (OA) is a valuable application of inertial measurement units (IMUs) in the remote monitoring of patients. This study aimed to employ the Fourier representation of IMU signals to differentiate between individuals with and without knee OA. We included 27 patients with unilateral knee osteoarthritis (15 females) and 18 healthy controls (11 females). Gait acceleration signals were recorded during overground walking. We obtained the frequency features of the signals using the Fourier transform. The logistic LASSO regression was employed on the frequency domain features as well as the participant’s age, sex, and BMI to distinguish between the acceleration data from individuals with and without knee OA. The model’s accuracy was estimated by 10-fold cross-validation. The frequency contents of the signals were different between the two groups. The average accuracy of the classification model using the frequency features was 0.91 ± 0.01. The distribution of the selected features in the final model differed between patients with different severity of knee OA. In this study, we demonstrated that using logistic LASSO regression on the Fourier representation of acceleration signals can accurately determine the presence of knee OA. Full article
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17 pages, 5805 KiB  
Article
Biomimetic Tendon-Based Mechanism for Finger Flexion and Extension in a Soft Hand Exoskeleton: Design and Experimental Assessment
by Mohamed H. Abdelhafiz, Lotte N. S. Andreasen Struijk, Strahinja Dosen and Erika G. Spaich
Sensors 2023, 23(4), 2272; https://doi.org/10.3390/s23042272 - 17 Feb 2023
Cited by 4 | Viewed by 3076
Abstract
This study proposes a bioinspired exotendon routing configuration for a tendon-based mechanism to provide finger flexion and extension that utilizes a single motor to reduce the complexity of the system. The configuration was primarily inspired by the extrinsic muscle–tendon units of the human [...] Read more.
This study proposes a bioinspired exotendon routing configuration for a tendon-based mechanism to provide finger flexion and extension that utilizes a single motor to reduce the complexity of the system. The configuration was primarily inspired by the extrinsic muscle–tendon units of the human musculoskeletal system. The function of the intrinsic muscle–tendon units was partially compensated by adding a minor modification to the configuration of the extrinsic units. The finger kinematics produced by this solution during flexion and extension were experimentally evaluated on an artificial finger and compared to that obtained using the traditional mechanism, where one exotendon was inserted at the distal phalanx. The experiments were conducted on nine healthy subjects who wore a soft exoskeleton glove equipped with the novel tendon mechanism. Contrary to the traditional approach, the proposed mechanism successfully prevented the hyperextension of the distal interphalangeal (DIP) and the metacarpophalangeal (MCP) joints. During flexion, the DIP joint angles produced by the novel mechanism were smaller than the angles generated by the traditional approach for the same proximal interphalangeal (PIP) joint angles. This provided a flexion trajectory closer to the voluntary flexion motion and avoided straining the interphalangeal coupling between the DIP and PIP joints. Finally, the proposed solution generated similar trajectories when applied to a stiff artificial finger (simulating spasticity). The results, therefore, demonstrate that the proposed approach is indeed an effective solution for the envisioned soft hand exoskeleton system. Full article
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15 pages, 4326 KiB  
Article
Hybrid Target Selections by ”Hand Gestures + Facial Expression” for a Rehabilitation Robot
by Yi Han, Xiangliang Zhang, Ning Zhang, Shuguang Meng, Tao Liu, Shuoyu Wang, Min Pan, Xiufeng Zhang and Jingang Yi
Sensors 2023, 23(1), 237; https://doi.org/10.3390/s23010237 - 26 Dec 2022
Cited by 1 | Viewed by 1894
Abstract
In this study we propose a “hand gesture + face expression” human machine interaction technique, and apply this technique to bedridden rehabilitation robot. “Hand gesture + Facial expression” interactive technology combines the input mode of gesture and facial expression perception. It involves seven [...] Read more.
In this study we propose a “hand gesture + face expression” human machine interaction technique, and apply this technique to bedridden rehabilitation robot. “Hand gesture + Facial expression” interactive technology combines the input mode of gesture and facial expression perception. It involves seven basic facial expressions that can be used to determine a target selecting task, while hand gestures are used to control a cursor’s location. A controlled experiment was designed and conducted to evaluate the effectiveness of the proposed hybrid technology. A series of target selecting tasks with different target widths and layouts were designed to examine the recognition accuracy of hybrid control gestures. An interactive experiment applied to a rehabilitation robot is designed to verify the feasibility of this interactive technology applied to rehabilitation robots. The experimental results show that the “hand + facial expression” interactive gesture has strong robustness, which can provide a novel guideline for designing applications in VR interfaces, and it can be applied to the rehabilitation robots. Full article
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