Thermal Cameras for Continuous and Contactless Respiration Monitoring.

Continuous respiration monitoring is an important tool in assessing the patient's health and diagnosing pulmonary, cardiovascular, and sleep-related breathing disorders. Various techniques and devices, both contact and contactless, can be used to monitor respiration. Each of these techniques can provide different types of information with varying accuracy.

Speckle Vibrometry for Contactless Instantaneous Heart Rate and Respiration Rate Monitoring on Mechanically Ventilated Patients.

: Contactless monitoring of instantaneous heart rate and respiration rate has a significant clinical relevance. This work aims to use Speckle Vibrometry (i.e.

Overnight Sleep Staging Using Chest-Worn Accelerometry.

Overnight sleep staging is an important part of the diagnosis of various sleep disorders. Polysomnography is the gold standard for sleep staging, but less-obtrusive sensing modalities are of emerging interest. Here, we developed and validated an algorithm to perform "proxy" sleep staging using cardiac and respiratory signals derived from a chest-worn accelerometer.

Quantitative validation of the suprasternal pressure signal to assess respiratory effort during sleep.

Intra-esophageal pressure (Pes) measurement is the recommended gold standard to quantify respiratory effort during sleep, but used to limited extent in clinical practice due to multiple practical drawbacks. Respiratory inductance plethysmography belts (RIP) in conjunction with oronasal airflow are the accepted substitute in polysomnographic systems (PSG) thanks to a better usability, although they are partial views on tidal volume and flow rather than true respiratory effort and are often used without calibration. In their place, the pressure variations measured non-invasively at the suprasternal notch (SSP) may provide a better measure of effort.

Maximum a posteriori detection of heartbeats from a chest-worn accelerometer.

. Unobtrusive long-term monitoring of cardiac parameters is important in a wide variety of clinical applications, such as the assesment of acute illness severity and unobtrusive sleep monitoring. Here we determined the accuracy and robustness of heartbeat detection by an accelerometer worn on the chest.

Predicting elbow load based on individual pelvis and trunk (inter)segmental rotations in fastball pitching.

The baseball pitch is a repetitive, full-body throwing motion that exposes the elbow to significant loads, leading to a high incidence of elbow injuries. Elbow injuries in pitching are often attributed to high external valgus torques as these are generally considered to be a good proxy for the load on the Ulnar Collateral Ligament. The aim of the study is to contribute to elbow load monitoring by developing a prediction model based on the pelvis and trunk peak angular velocities and their separation time.

Deep transfer learning for automated single-lead EEG sleep staging with channel and population mismatches.

Automated sleep staging using deep learning models typically requires training on hundreds of sleep recordings, and pre-training on public databases is therefore common practice. However, suboptimal sleep stage performance may occur from mismatches between source and target datasets, such as differences in population characteristics (e.g.

Performance of cardiorespiratory-based sleep staging in patients using beta blockers.

Study Objectives: Automatic sleep staging based on cardiorespiratory signals from home sleep monitoring devices holds great clinical potential. Using state-of-the-art machine learning, promising performance has been reached in patients with sleep disorders. However, it is unknown whether performance would hold in individuals with potentially altered autonomic physiology, for example under the influence of medication.

Studying sleep: towards the identification of hypnogram features that drive expert interpretation.

Study Objectives: Hypnograms contain a wealth of information and play an important role in sleep medicine. However, interpretation of the hypnogram is a difficult task and requires domain knowledge and "clinical intuition." This study aimed to uncover which features of the hypnogram drive interpretation by physicians.

A sleep stage estimation algorithm based on cardiorespiratory signals derived from a suprasternal pressure sensor.

Automatic estimation of sleep structure is an important aspect in moving sleep monitoring from clinical laboratories to people's homes. However, the transition to more portable systems should not happen at the expense of important physiological signals, such as respiration. Here, we propose the use of cardiorespiratory signals obtained by a suprasternal pressure (SSP) sensor to estimate sleep stages.

Speckle Vibrometry for Instantaneous Heart Rate Monitoring.

Instantaneous heart rate (IHR) has been investigated for sleep applications, such as sleep apnea detection and sleep staging. To ensure the comfort of the patient during sleep, it is desirable for IHR to be measured in a contact-free fashion. In this work, we use speckle vibrometry (SV) to perform on-skin and on-textile IHR monitoring in a sleep setting.

Automated sleep staging in people with intellectual disabilities using heart rate and respiration variability.

Background: People with intellectual disabilities (ID) have a higher risk of sleep disorders. Polysomnography (PSG) remains the diagnostic gold standard in sleep medicine. However, PSG in people with ID can be challenging, as sensors can be burdensome and have a negative influence on sleep.

A computationally efficient algorithm for wearable sleep staging in clinical populations.

This study describes a computationally efficient algorithm for 4-class sleep staging based on cardiac activity and body movements. Using an accelerometer to calculate gross body movements and a reflective photoplethysmographic (PPG) sensor to determine interbeat intervals and a corresponding instantaneous heart rate signal, a neural network was trained to classify between wake, combined N1 and N2, N3 and REM sleep in epochs of 30 s. The classifier was validated on a hold-out set by comparing the output against manually scored sleep stages based on polysomnography (PSG).

Contactless Camera-Based Sleep Staging: The HealthBed Study.

Polysomnography (PSG) remains the gold standard for sleep monitoring but is obtrusive in nature. Advances in camera sensor technology and data analysis techniques enable contactless monitoring of heart rate variability (HRV). In turn, this may allow remote assessment of sleep stages, as different HRV metrics indirectly reflect the expression of sleep stages.

Individualised Ball Speed Prediction in Baseball Pitching Based on IMU Data.

Ball velocity is considered an important performance measure in baseball pitching. Proper pitching mechanics play an important role in both maximising ball velocity and injury-free participation of baseball pitchers. However, an individual pitcher's characteristics display individuality and may contribute to velocity imparted to the ball.

Dynamical indicators of resilience from physiological time series in geriatric inpatients: Lessons learned.

The concept of physical resilience may help geriatric medicine objectively assess patients' ability to 'bounce back' from future health challenges. Indicators putatively forecasting resilience have been developed under two paradigms with different perspectives: Critical Slowing Down and Loss of Complexity. This study explored whether these indicators validly reflect the construct of resilience in geriatric inpatients.

Quality of Care Perceived by Older Patients and Caregivers in Integrated Care Pathways With Interviewing Assistance From a Social Robot: Noninferiority Randomized Controlled Trial.

Background: Society is facing a global shortage of 17 million health care workers, along with increasing health care demands from a growing number of older adults. Social robots are being considered as solutions to part of this problem.

Objective: Our objective is to evaluate the quality of care perceived by patients and caregivers for an integrated care pathway in an outpatient clinic using a social robot for patient-reported outcome measure (PROM) interviews versus the currently used professional interviews.

Exploring the views of successful applicants for medical school about gender medicine using a gender-sensitive video assignment.

Background: Sex and gender influence health and disease outcomes, therefore, doctors should be able to deliver gender-sensitive care. To train gender-sensitive doctors, relevant sex and gender differences have to be included in medical education. In order to develop appealing, relevant, and effective education for undergraduate medical students, education should be tailored to students' level and anticipated on their ideas and assumptions.

Measurement of Dynamical Resilience Indicators Improves the Prediction of Recovery Following Hospitalization in Older Adults.

Objectives: Acute illnesses and subsequent hospital admissions present large health stressors to older adults, after which their recovery is variable. The concept of physical resilience offers opportunities to develop dynamical tools to predict an individual's recovery potential. This study aimed to investigate if dynamical resilience indicators based on repeated physical and mental measurements in acutely hospitalized geriatric patients have added value over single baseline measurements in predicting favorable recovery.

Robot for health data acquisition among older adults: a pilot randomised controlled cross-over trial.

Background /objectives: Healthcare professionals (HCP) are confronted with an increased demand for assessments of important health status measures, such as patient-reported outcome measurements (PROM), and the time this requires. The aim of this study was to investigate the effectiveness and acceptability of using an HCP robot assistant, and to test the hypothesis that a robot can autonomously acquire PROM data from older adults.

Design: A pilot randomised controlled cross-over study where a social robot and a nurse administered three PROM questionnaires with a total of 52 questions.

Assessment of lower arm movements using one inertial sensor.

Reduction of the number of sensors needed to evaluate arm movements, makes a system for the assessment of human body movements more suitable for clinical practice and daily life assessments. In this study, we propose an algorithm to reconstruct lower arm orientation, velocity and position, based on a sensing system which consists of only one inertial measurement unit (IMU) to the forearm. Lower arm movements were reconstructed using a single IMU and assuming that within a measurement there are moments without arm movements.

Usability Evaluations of a Wearable Inertial Sensing System and Quality of Movement Metrics for Stroke Survivors by Care Professionals.

Background: Inertial motion capture systems are used in many applications such as measuring the movement quality in stroke survivors. The absence of clinical effectiveness and usability evidence in these assistive technologies into rehabilitation has delayed the transition of research into clinical practice. Recently, a new inertial motion capture system was developed in a project, called INTERACTION, to objectively measure the quality of movement (QoM) in stroke survivors during daily-life activity.

Successfully sustaining sex and gender issues in undergraduate medical education: a case study.

Although several projects have addressed the importance of gender health issues in medical education, the sustainability of change efforts in medical education has rarely been addressed. Understanding the possible facilitators or barriers to sustainability may help to develop future interventions that are effective in maintaining gender health issues as a topic in medical curricula. The aim of this study is to provide a longitudinal evaluation of changes regarding gender health issues that occurred in the past decade and the factors that influenced this process.

Analysis of Balance during Functional Walking in Stroke Survivors.

Background: An important objective of rehabilitation care is to regain adequate balance function to safely ambulate in community. However, in rehabilitation practice, it remains unclear if a stroke survivor functionally recovers by restitution or by learning to compensate for the lack of restoration of body function. Aim of this study is to propose and evaluate methods for the objective evaluation of balance during functional walking in stroke survivors.

Ambulatory assessment of walking balance after stroke using instrumented shoes.

Background: For optimal guidance of walking rehabilitation therapy of stroke patients in an in-home setting, a small and easy to use wearable system is needed. In this paper we present a new shoe-integrated system that quantifies walking balance during activities of daily living and is not restricted to a lab environment. Quantitative parameters were related to clinically assessed level of balance in order to assess the additional information they provide.