Search Results (20)

Diabetes Mellitus is a significant global health issue, affecting over half a billion people worldwide. Current glucose monitoring methods are invasive, painful, and require skilled application, highlighting the need for the development of effective, non-invasive, and easy to use methods. This paper presents our work on the design, development, and evaluation of a non-invasive blood glucose monitoring system, utilizing Near-Infrared Spectroscopy technique for glucose monitoring. The proposed system comprises a MAX30102 biosensor connected to an ESP32 microcontroller. The biosensor captures the photoplethysmogram signals, which are then processed by a microcontroller to evaluate blood glucose level. In order to increase the accuracy of the results, we have incorporated linear regression with Clarke Error Grid Analysis to calibrate our system. The linear regression model is trained by comparing the results obtained through the developed system with that of a commercial off-the-self invasive device. The glucose levels obtained through the developed system are displayed in real-time on an Organic LED (OLED) screen and simultaneously uploaded to a cloud server via Internet of Things for remote monitoring. To validate the performance of the proposed system, we have compared the performance metrics of our system against existing solutions published in the literature. Performance comparisons show that our system achieves a reasonably good accuracy with a root mean square error of 13.8 mg/dL and a mean absolute relative difference of 12%. The proposed system offers a painless and convenient solution, potentially improving glucose monitoring for patients. Full article

Pain and knee stiffness are common problems following total knee replacement surgery, with 10–20% of patients reporting dissatisfaction following their procedure. A remote assessment of knee stiffness could improve outcomes through continuous monitoring, facilitating timely intervention. Using machine learning algorithms, computer vision can extract joint angles from video footage, offering a method to monitor knee range of motion in patients’ homes. This study outlines a protocol to provide proof of concept and validate a computer vision-based approach for measuring knee range of motion in individuals who have undergone total knee replacement. The study also explores the feasibility of integrating this technology into clinical practice, enhancing post-operative care. The study is divided into three components: carrying out focus groups, validating the computer vision-based software, and home testing. The focus groups will involve five people who underwent total knee replacement and ten healthcare professionals or carers who will discuss the deployment of the software in clinical settings. For the validation phase, 60 participants, including 30 patients who underwent total knee replacement surgery five to nine weeks prior and 30 healthy controls, will be recruited. The participants will perform five tasks, including the sit-to-stand test, where knee range of motion will be measured using computer vision-based markerless motion capture software, marker-based motion capture, and physiotherapy assessments. The accuracy and reliability of the software will be evaluated against these established methods. Participants will perform the sit-to-stand task at home. This will allow for a comparison between home-recorded and lab-based data. The findings from this study have the potential to significantly enhance the monitoring of knee stiffness following total knee replacement. By providing accurate, remote measurements and enabling the early detection of issues, this technology could facilitate timely referrals to non-surgical treatments, ultimately reducing the need for costly and invasive procedures to improve knee range of motion. Full article

The excessive use of electronic devices for prolonged periods has led to problems such as neck pain and pressure injury in sedentary people. If not detected and corrected early, these issues can cause serious risks to physical health. Detectors for generic objects cannot adequately capture such subtle neck behaviors, resulting in missed detections. In this paper, we explore a deep learning-based solution for detecting abnormal behavior of the neck and propose a model called NABNet that combines object detection based on YOLOv5s with pose estimation based on Lightweight OpenPose. NABNet extracts the detailed behavior characteristics of the neck from global to local and detects abnormal behavior by analyzing the angle of the data. We deployed NABNet on the cloud and edge devices to achieve remote monitoring and abnormal behavior alarms. Finally, we applied the resulting NABNet-based IoT system for abnormal behavior detection in order to evaluate its effectiveness. The experimental results show that our system can effectively detect abnormal neck behavior and raise alarms on the cloud platform, with the highest accuracy reaching 94.13%. Full article

Treatment for breast cancer (BC) can lead to debilitating symptoms that can reduce outcomes and quality of life (QoL). Symptom surveillance using a remote symptom monitoring (RSM) platform enables the capture and reporting of patient-reported outcomes (PROs) from home. Women with BC used an RSM platform to complete weekly surveys and report any symptoms experienced during treatment. Symptoms reported as moderate/severe generated alerts to the clinical team. Clinical actions in response to the alert were captured. Results highlighted the value of data generated from a PRO-generated alert system to characterize longitudinal symptom burden and QoL in real-world BC practice, particularly in patients with poor functional status. The most prevalent symptoms that resulted in alerts were pain, nausea/vomiting, neuropathy, fatigue, and constipation. Most women reported one or more moderate/severe symptoms that generated an alert with an average of two alerts per week. Patients with frail status had more alerts, worse QoL and higher treatment bother, indicating that frail patients may benefit from continuous monitoring of symptoms, function, and QoL over time. A case study of patients without pre-existing peripheral neuropathy showed the rapid trajectory from the first report of mild neuropathy until alerts were generated, making a case for early intervention. Full article

Objectives: To determine whether allied health interventions delivered using telehealth provide similar or better outcomes for patients compared with traditional face-to-face delivery modes. Study design: A rapid systematic review using the Cochrane methodology to extract eligible randomized trials. Eligible trials: Trials were eligible for inclusion if they compared a comparable dose of face-to-face to telehealth interventions delivered by a neuropsychologist, occupational therapist, physiotherapist, podiatrist, psychologist, and/or speech pathologist; reported patient-level outcomes; and included adult participants. Data sources: MEDLINE, CENTRAL, CINAHL, and EMBASE databases were first searched from inception for systematic reviews and eligible trials were extracted from these systematic reviews. These databases were then searched for randomized clinical trials published after the date of the most recent systematic review search in each discipline (2017). The reference lists of included trials were also hand-searched to identify potentially missed trials. The risk of bias was assessed using the Cochrane Risk of Bias Tool Version 1. Data Synthesis: Fifty-two trials (62 reports, n = 4470) met the inclusion criteria. Populations included adults with musculoskeletal conditions, stroke, post-traumatic stress disorder, depression, and/or pain. Synchronous and asynchronous telehealth approaches were used with varied modalities that included telephone, videoconferencing, apps, web portals, and remote monitoring, Overall, telehealth delivered similar improvements to face-to-face interventions for knee range, Health-Related Quality of Life, pain, language function, depression, anxiety, and Post-Traumatic Stress Disorder. This meta-analysis was limited for some outcomes and disciplines such as occupational therapy and speech pathology. Telehealth was safe and similar levels of satisfaction and adherence were found across modes of delivery and disciplines compared to face-to-face interventions. Conclusions: Many allied health interventions are equally as effective as face-to-face when delivered via telehealth. Incorporating telehealth into models of care may afford greater access to allied health professionals, however further comparative research is still required. In particular, significant gaps exist in our understanding of the efficacy of telehealth from podiatrists, occupational therapists, speech pathologists, and neuropsychologists. Protocol Registration Number: PROSPERO (CRD42020203128). Full article

Shoulder pain represents the most frequently reported musculoskeletal disorder, often leading to significant functional impairment and pain, impacting quality of life. Home-based rehabilitation programs offer a more accessible and convenient solution for an effective shoulder disorder treatment, addressing logistical and financial constraints associated with traditional physiotherapy. The aim of this systematic review is to report the monitoring devices currently proposed and tested for shoulder rehabilitation in home settings. The research question was formulated using the PICO approach, and the PRISMA guidelines were applied to ensure a transparent methodology for the systematic review process. A comprehensive search of PubMed and Scopus was conducted, and the results were included from 2014 up to 2023. Three different tools (i.e., the Rob 2 version of the Cochrane risk-of-bias tool, the Joanna Briggs Institute (JBI) Critical Appraisal tool, and the ROBINS-I tool) were used to assess the risk of bias. Fifteen studies were included as they fulfilled the inclusion criteria. The results showed that wearable systems represent a promising solution as remote monitoring technologies, offering quantitative and clinically meaningful insights into the progress of individuals within a rehabilitation pathway. Recent trends indicate a growing use of low-cost, non-intrusive visual tracking devices, such as camera-based monitoring systems, within the domain of tele-rehabilitation. The integration of home-based monitoring devices alongside traditional rehabilitation methods is acquiring significant attention, offering broader access to high-quality care, and potentially reducing healthcare costs associated with in-person therapy. Full article

Digital health tracking is a source of valuable insights for public health research and consumer health technology. The brain is the most complex organ, containing information about psychophysical and physiological biomarkers that correlate with health. Specifically, recent developments in electroencephalogram (EEG), functional near-infra-red spectroscopy (fNIRS), and photoplethysmography (PPG) technologies have allowed the development of devices that can remotely monitor changes in brain activity. The inclusion criteria for the papers in this review encompassed studies on self-applied, remote, non-invasive neuroimaging techniques (EEG, fNIRS, or PPG) within healthcare applications. A total of 23 papers were reviewed, comprising 17 on using EEGs for remote monitoring and 6 on neurofeedback interventions, while no papers were found related to fNIRS and PPG. This review reveals that previous studies have leveraged mobile EEG devices for remote monitoring across the mental health, neurological, and sleep domains, as well as for delivering neurofeedback interventions. With headsets and ear-EEG devices being the most common, studies found mobile devices feasible for implementation in study protocols while providing reliable signal quality. Moderate to substantial agreement overall between remote and clinical-grade EEGs was found using statistical tests. The results highlight the promise of portable brain-imaging devices with regard to continuously evaluating patients in natural settings, though further validation and usability enhancements are needed as this technology develops. Full article

Juvenile idiopathic arthritis can be influenced by pain, medication adherence, and physical activity. A new digital health intervention, InteractiveClinics, aims to monitor these modifiable risk factors. Twelve children, aged 10 to 18 years, received daily notifications on a smartwatch to record their pain levels and take their medications, using a customised mobile app synchronised to a secure web-based platform. Daily physical activity levels were automatically recorded by wearing a smartwatch. Using a quantitative descriptive research design, feasibility and user adoption were evaluated. The web-based data revealed the following: Pain: mean app usage: 68% (SD 30, range: 28.6% to 100%); pain score: 2.9 out of 10 (SD 1.8, range: 0.3 to 6.2 out of 10). Medication adherence: mean app usage: 20.7% (SD, range: 0% to 71.4%), recording 39% (71/182) of the expected daily and 37.5% (3/8) of the weekly medications. Pro-re-nata (PRN) medication monitoring: 33.3% (4/12), one to six additional medications (mean 3.5, SD 2.4) for 2–6 days. Physical activity: watch wearing behaviour: 69.7% (439/630), recording low levels of moderate-to-vigorous physical activity (mean: 11.8, SD: 13.5 min, range: 0–47 min). To conclude, remote monitoring of real-time data is feasible. However, further research is needed to increase adoption rates among children. Full article

Pain continues to be a significant problem for cancer patients, and the impact of a population-based strategy on their experiences is not completely understood. Our study aimed to determine the impact of palliative care on mitigating pain and its associated effects in determining the quality of life (QoL) among colon cancer outpatients. Six collection databases were used to perform a structured systematic review of the available literature, considering all papers published between the year 2000 and February 2023. PRISMA guidelines were adopted in our study, and a total of 9792 papers were evaluated. However, only 126 articles met the inclusion criteria. A precise diagnosis of disruptive colorectal cancer (CRC) pain disorders among patients under palliative care is necessary to mitigate it and its associated effects, enhance health, promote life expectancy, increase therapeutic responsiveness, and decrease comorbidity complications. Physical activities, the use of validated pain assessment tools, remote outpatient education and monitoring, chemotherapeutic pain reduction strategies, music and massage therapies, and bridging social isolation gaps are essential in enhancing QoL. We recommend and place a strong emphasis on the adoption of online training/or coaching programs and the integration of formal and informal palliative care systems for maximum QoL benefits among CRC outpatients. Full article

Introduction: Chronic conditions such as stroke, Parkinson’s disease, spinal cord injury, multiple sclerosis, vestibular disorders, chronic pain, arthritis, diabetes, chronic obstructive pulmonary disease (COPD), and heart disease are leading causes of disability among middle-aged and older adults. While evidence-based treatment can optimize clinical outcomes, few people with chronic conditions engage in the recommended levels of exercise for clinical improvement and successful management of their condition. Rehabilitation technologies that can augment therapeutic care—i.e., exoskeletons, virtual/augmented reality, and remote monitoring—offer the opportunity to bring evidence-based rehabilitation into homes. Successful integration of rehabilitation techniques at home could help recovery and access and foster long term self-management. However, widespread uptake of technology in rehabilitation is still limited, leaving many technologies developed but not adopted. Methods: In this narrative review, clinical need, efficacy, and obstacles and suggestions for implementation are discussed. The use of three technologies is reviewed in the management of the most prevalent chronic diseases that utilize rehabilitation services, including common neurological, musculoskeletal, metabolic, pulmonary, and cardiac conditions. The technologies are (i) exoskeletons, (ii) virtual and augmented reality, and (iii) remote monitoring. Results: Effectiveness evidence backing the use of technology in rehabilitation is growing but remains limited by high heterogeneity, lack of long-term outcomes, and lack of adoption outcomes. Conclusion: While rehabilitation technologies bring opportunities to bridge the gap between clinics and homes, there are many challenges with adoption. Hybrid effectiveness and implementation trials are a possible path to successful technology development and adoption. Full article

Aim: Since beds are unavailable, we prospectively investigated whether early hospital discharge will be safe and useful in patients hospitalized for COVID-19, regardless of their need for home oxygen therapy. Population and Methods: Extending the initial inclusion criteria, 62 patients were included and 51 benefited from home telemonitoring, mainly assessing clinical parameters (blood pressure, heart rate, respiratory rate, dyspnea, temperature) and peripheral saturation (SpO₂) at follow-up. Results: 47% of the patients were older than 65 years; 63% needed home oxygen therapy and/or presented with more than one comorbidity. At home, the mean time to dyspnea and tachypnea resolutions ranged from 21 to 24 days. The mean oxygen-weaning duration was 13.3 ± 10.4 days, and the mean SpO₂ was 95.7 ± 1.6%. The nurses and/or doctors managed 1238 alerts. Two re-hospitalizations were required, related to transient chest pain or pulmonary embolism, but no death occurred. Patient satisfaction was good, and 743 potential days of hospitalization were saved for other patients. Conclusion: The remote monitoring of vital parameters and symptoms is safe, allowing for early hospital discharge in patients hospitalized for COVID-19, whether or not home oxygen therapy was required. Oxygen tapering outside the hospital allowed for a greater reduction in hospital stay. Randomized controlled trials are necessary to confirm this beneficial effect. Full article

Background and Objectives: Remote patient monitoring (RPM) of vital signs and symptoms for lung transplant recipients (LTRs) has become increasingly relevant in many situations. Nevertheless, RPM research integrating multisensory home monitoring in LTRs is scarce. We developed a novel multisensory home monitoring device and tested it in the context of COVID-19 vaccinations. We hypothesize that multisensory RPM and smartphone-based questionnaire feedback on signs and symptoms will be well accepted among LTRs. To assess the usability and acceptability of a remote monitoring system consisting of wearable devices, including home spirometry and a smartphone-based questionnaire application for symptom and vital sign monitoring using wearable devices, during the first and second SARS-CoV-2 vaccination. Materials and Methods: Observational usability pilot study for six weeks of home monitoring with the COVIDA Desk for LTRs. During the first week after the vaccination, intensive monitoring was performed by recording data on physical activity, spirometry, temperature, pulse oximetry and self-reported symptoms, signs and additional measurements. During the subsequent days, the number of monitoring assessments was reduced. LTRs reported on their perceptions of the usability of the monitoring device through a purpose-designed questionnaire. Results: Ten LTRs planning to receive the first COVID-19 vaccinations were recruited. For the intensive monitoring study phase, LTRs recorded symptoms, signs and additional measurements. The most frequent adverse events reported were local pain, fatigue, sleep disturbance and headache. The duration of these symptoms was 5–8 days post-vaccination. Adherence to the main monitoring devices was high. LTRs rated usability as high. The majority were willing to continue monitoring. Conclusions: The COVIDA Desk showed favorable technical performance and was well accepted by the LTRs during the vaccination phase of the pandemic. The feasibility of the RPM system deployment was proven by the rapid recruitment uptake, technical performance (i.e., low number of errors), favorable user experience questionnaires and detailed individual user feedback. Full article

Remote patient monitoring is one of the most reliable choices for the availability of health care services for the elderly and/or chronically ill. Rehabilitation requires the exact and medically correct completion of physiotherapy activities. This paper presents BiomacVR, a virtual reality (VR)-based rehabilitation system that combines a VR physical training monitoring environment with upper limb rehabilitation technology for accurate interaction and increasing patients’ engagement in rehabilitation training. The system utilises a deep learning motion identification model called Convolutional Pose Machine (CPM) that uses a stacked hourglass network. The model is trained to precisely locate critical places in the human body using image sequences collected by depth sensors to identify correct and wrong human motions and to assess the effectiveness of physical training based on the scenarios presented. This paper presents the findings of the eight most-frequently used physical training exercise situations from post-stroke rehabilitation methodology. Depth sensors were able to accurately identify key parameters of the posture of a person performing different rehabilitation exercises. The average response time was 23 ms, which allows the system to be used in real-time applications. Furthermore, the skeleton features obtained by the system are useful for discriminating between healthy (normal) subjects and subjects suffering from lower back pain. Our results confirm that the proposed system with motion recognition methodology can be used to evaluate the quality of the physiotherapy exercises of the patient and monitor the progress of rehabilitation and assess its effectiveness. Full article

Neurodegenerative diseases (NDDs) are among the 10 causes of death worldwide. The effects of NDDs, including irreversible motor impairments, have an impact not only on patients themselves but also on their families and social environments. One strategy to mitigate the pain of NDDs is to early identify and remotely monitor related motor impairments using wearable devices. Technological progress has contributed to reducing the hardware complexity of mobile devices while simultaneously improving their efficiency in terms of data collection and processing and energy consumption. However, perhaps the greatest challenges of current mobile devices are to successfully manage the security and privacy of patient medical data and maintain reasonable costs with respect to the traditional patient consultation scheme. In this work, we conclude: (1) Falls are most monitored for Parkinson’s disease, while tremors predominate in epilepsy and Alzheimer’s disease. These findings will provide guidance for wearable device manufacturers to strengthen areas of opportunity that need to be addressed, and (2) Of the total universe of commercial wearables devices that are available on the market, only a few have FDA approval, which means that there is a large number of devices that do not safeguard the integrity of the users who use them. Full article

Precision swine production can benefit from autonomous, noninvasive, and affordable devices that conduct frequent checks on the well-being status of pigs. Here, we present a remote monitoring tool for the objective measurement of some behavioral indicators that may help in assessing the health and welfare status—namely, posture, gait, vocalization, and external temperature. The multiparameter electronic sensor board is characterized by laboratory measurements and by animal tests. Relevant behavioral health indicators are discussed for implementing machine learning algorithms and decision support tools to detect animal lameness, lethargy, pain, injury, and distress. The roadmap for technology adoption is also discussed, along with challenges and the path forward. The presented technology can potentially lead to efficient management of farm animals, targeted focus on sick animals, medical cost savings, and less use of antibiotics. Full article