An Analysis of Fluid Intake Assessment Approaches for Fluid Intake Monitoring System.

Monitoring fluid intake is essential to help people manage their individual fluid intake behaviors and achieve adequate hydration. Previous studies of fluid intake assessment approaches based on inertial sensors can be categorized into wrist-worn-based and smart-container-based approaches. This study aims to analyze wrist-worn-based and smart-container-based fluid intake assessment approaches using inertial sensors.

Inertial Measurement Unit-Based Romberg Test for Assessing Adults With Vestibular Hypofunction.

This work aims to explore the utility of wearable inertial measurement units (IMUs) for quantifying movement in Romberg tests and investigate the extent of movement in adults with vestibular hypofunction (VH). A cross-sectional study was conducted at an academic tertiary medical center between March 2021 and April 2022. Adults diagnosed with unilateral vestibular hypofunction (UVH) or bilateral vestibular hypofunction (BVH) were enrolled in the VH group.

Multi-Task Learning U-Net for Functional Shoulder Sub-Task Segmentation.

The assessment of a frozen shoulder (FS) is critical for evaluating outcomes and medical treatment. Analysis of functional shoulder sub-tasks provides more crucial information, but current manual labeling methods are time-consuming and prone to errors. To address this challenge, we propose a deep multi-task learning (MTL) U-Net to provide an automatic and reliable functional shoulder sub-task segmentation (STS) tool for clinical evaluation in FS.

Domain-Adaptive Fall Detection Using Deep Adversarial Training.

Fall detection (FD) systems are important assistive technologies for healthcare that can detect emergency fall events and alert caregivers. However, it is not easy to obtain large-scale annotated fall events with various specifications of sensors or sensor positions during the implementation of accurate FD systems. Moreover, the knowledge obtained through machine learning has been restricted to tasks in the same domain.

Multiphase Identification Algorithm for Fall Recording Systems Using a Single Wearable Inertial Sensor.

Fall-related information can help clinical professionals make diagnoses and plan fall prevention strategies. The information includes various characteristics of different fall phases, such as falling time and landing responses. To provide the information of different phases, this pilot study proposes an automatic multiphase identification algorithm for phase-aware fall recording systems.

Automatic Functional Shoulder Task Identification and Sub-task Segmentation Using Wearable Inertial Measurement Units for Frozen Shoulder Assessment.

Advanced sensor technologies have been applied to support frozen shoulder assessment. Sensor-based assessment tools provide objective, continuous and quantitative information for evaluation and diagnosis. However, the current tools for assessment of functional shoulder tasks mainly rely on manual operation.

Fluid Intake Monitoring System Using a Wearable Inertial Sensor for Fluid Intake Management.

Fluid intake is important for people to maintain body fluid homeostasis. Inadequate fluid intake leads to negative health consequences, such as headache, dizziness and urolithiasis. However, people in busy lifestyles usually forget to drink sufficient water and neglect the importance of fluid intake.

Subtask Segmentation of Timed Up and Go Test for Mobility Assessment of Perioperative Total Knee Arthroplasty.

Total knee arthroplasty (TKA) is one of the most common treatments for people with severe knee osteoarthritis (OA). The accuracy of outcome measurements and quantitative assessments for perioperative TKA is an important issue in clinical practice. Timed up and go (TUG) tests have been validated to measure basic mobility and balance capabilities.

Multi-Sensor Fusion Approach for Improving Map-Based Indoor Pedestrian Localization.

The interior space of large-scale buildings, such as hospitals, with a variety of departments, is so complicated that people may easily lose their way while visiting. Difficulties in wayfinding can cause stress, anxiety, frustration and safety issues to patients and families. An indoor navigation system including route planning and localization is utilized to guide people from one place to another.

Time-dependent analysis of dosage delivery information for patient-controlled analgesia services.

Pain relief always plays the essential part of perioperative care and an important role of medical quality improvement. Patient-controlled analgesia (PCA) is a method that allows a patient to self-administer small boluses of analgesic to relieve the subjective pain. PCA logs from the infusion pump consisted of a lot of text messages which record all events during the therapies.

Data Collection and Analysis Using Wearable Sensors for Monitoring Knee Range of Motion after Total Knee Arthroplasty.

Total knee arthroplasty (TKA) is the most common treatment for degenerative osteoarthritis of that articulation. However, either in rehabilitation clinics or in hospital wards, the knee range of motion (ROM) can currently only be assessed using a goniometer. In order to provide continuous and objective measurements of knee ROM, we propose the use of wearable inertial sensors to record the knee ROM during the recovery progress.

Novel Hierarchical Fall Detection Algorithm Using a Multiphase Fall Model.

Falls are the primary cause of accidents for the elderly in the living environment. Reducing hazards in the living environment and performing exercises for training balance and muscles are the common strategies for fall prevention. However, falls cannot be avoided completely; fall detection provides an alarm that can decrease injuries or death caused by the lack of rescue.

Significant Change Spotting for Periodic Human Motion Segmentation of Cleaning Tasks Using Wearable Sensors.

The proportion of the aging population is rapidly increasing around the world, which will cause stress on society and healthcare systems. In recent years, advances in technology have created new opportunities for automatic activities of daily living (ADL) monitoring to improve the quality of life and provide adequate medical service for the elderly. Such automatic ADL monitoring requires reliable ADL information on a fine-grained level, especially for the status of interaction between body gestures and the environment in the real-world.

Respiratory Rate Estimation by Using ECG, Impedance, and Motion Sensing in Smart Clothing.

The needs for light-weight and soft smart clothing in homecare have been rising since the past decade. Many smart textile sensors have been developed and applied to automatic physiological and user-centered environmental status recognition. In the present study, we propose wearable multi-sensor smart clothing for homecare monitoring based on an economic fabric electrode with high elasticity and low resistance.

Exercise Performance Measurement with Smartphone Embedded Sensor for Well-Being Management.

Regular physical activity reduces the risk of many diseases and improves physical and mental health. However, physical inactivity is widespread globally. Improving physical activity levels is a global concern in well-being management.

A Fuzzy Logic Prompting Mechanism Based on Pattern Recognition and Accumulated Activity Effective Index Using a Smartphone Embedded Sensor.

Sufficient physical activity can reduce many adverse conditions and contribute to a healthy life. Nevertheless, inactivity is prevalent on an international scale. Improving physical activity is an essential concern for public health.

Wearable sensor-based rehabilitation exercise assessment for knee osteoarthritis.

Since the knee joint bears the full weight load of the human body and the highest pressure loads while providing flexible movement, it is the body part most vulnerable and susceptible to osteoarthritis. In exercise therapy, the early rehabilitation stages last for approximately six weeks, during which the patient works with the physical therapist several times each week. The patient is afterwards given instructions for continuing rehabilitation exercise by him/herself at home.

An accumulated activity effective index for promoting physical activity: a design and development study in a mobile and pervasive health context.

Background: Increased physical activity has become a principal personal health goal worldwide because sufficient physical activity can reduce the risk of many adverse conditions. Motivating individuals to increase their levels of physical activity can increase life expectancy and contribute to a healthy life. Sharing and comparison of physical activity information by using the Internet, with fewer privacy concerns, might also help encourage people to promote and maintain sufficient physical activity.

A ZigBee-based location-aware fall detection system for improving elderly telecare.

Falls are the primary cause of accidents among the elderly and frequently cause fatal and non-fatal injuries associated with a large amount of medical costs. Fall detection using wearable wireless sensor nodes has the potential of improving elderly telecare. This investigation proposes a ZigBee-based location-aware fall detection system for elderly telecare that provides an unobstructed communication between the elderly and caregivers when falls happen.

A resident's behavior simulation model for nursing home healthcare services.

The design of elaborate healthcare services is becoming increasingly difficult in today's nursing home. In this work, we develop a model that simulates the nursing home residents' behavior to assist the facility planners in making fair and feasible management. Since a series of activities constituted one behavior, every activity is performed in a time interval and then starts next activity consequently.

A reliable transmission protocol for ZigBee-based wireless patient monitoring.

Patient monitoring systems are gaining their importance as the fast-growing global elderly population increases demands for caretaking. These systems use wireless technologies to transmit vital signs for medical evaluation. In a multihop ZigBee network, the existing systems usually use broadcast or multicast schemes to increase the reliability of signals transmission; however, both the schemes lead to significantly higher network traffic and end-to-end transmission delay.

An analysis of patient variables that influence intravenous patient-controlled analgesic use of morphine with quantile regression.

Background: Previous studies using linear regression analysis have shown that age, weight, gender, and the site of operation affect intravenous patient-controlled analgesia (IVPCA) narcotic use. However, there are inconsistent observations in the literature. The authors postulate that patient variables could have different effects at various doses of narcotics.

The relationship between lockout interval and requirement for patient-controlled epidural analgesia.

Background: Patient-controlled epidural analgesia (PCEA) with background infusion provides better analgesia than the use of a demand dose alone but might be associated with more consumption of PCEA solution and adverse effects. Therefore, we conducted this retrospective study to evaluate the influence of parameters of the drug delivery system on the PCEA requirements of patients receiving thoracic or upper abdominal surgeries.

Methods: Patients having operations involving the chest or upper abdomen with postoperative PCEA were included in the analyses.