No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Development of an internet of things (IoT)-based pill monitoring device for geriatric patients
... However, it currently lacks a data-sharing feature for communication between patients and healthcare professionals. Another similar study [106] developed a monitoring tablet device that employs an image processing algorithm to detect and count tablets. The system captures photos of the sealed tablets at regular intervals using a CMOS camera, and if a dose is missed, the software sends an email reminder to the patient. ...
... Non-invasive Environmental [94], [97], [98], [102], [84]- [89], [95], [96], [99]- [88], [99]- [101] [103], [111] [101], [104]- [106], [115], [116] ...
Cyber-physical systems (CPS) are recognized for their intelligence as they seamlessly interact with humans, enhancing the physical world through computation, communication, and control. Over the last few years, the evolution of CPS, including IoT components, has significantly impacted many facets of people’s lifestyles. It has been immersed in a wide range of services and applications in various areas, including manufacturing, healthcare, and energy. However, the interrelationship between the cyber and physical worlds gives rise to a multitude of research problems and challenges. In the healthcare field, for instance, CPS introduces complexities related to interoperability, privacy, data security, and real-time data processing with critical implications for the reliability and safety of medical processes. To address these challenges and harness the full potential of CPS in healthcare, this paper, through a comprehensive literature review, aims to discuss cutting-edge CPS technologies and solutions that hold promise for healthcare applications. To this end, we propose a comprehensive architectural model that can serve as a benchmark for implementing CPS in healthcare applications. This model thoroughly details how services, components, and technologies can be integrated to transform massive raw data collected from the physical world into valuable information for an enhanced decision-making process. Finally, a use case on healthcare CPS is presented, outlining its characteristics, the role that different technologies have played in its development, and the major challenges in implementing such systems successfully. This study provides a cohesive understanding of the role CPS can play in empowering healthcare while offering insights into the challenges, and future research trends.
... Among the numerous options, the application of ground-breaking advances in IoT technology has tremendous potential. A growing body of research supports the effectiveness of IoT-enabled devices and technological solutions in improving medication adherence among patients (Faisal et al., 2021;Orcioni et al., 2021;Pawar et al., 2021;Rane et al., 2023;Sahu et al., 2023). These IoT solutions include various tools, ranging from intelligent pillboxes and wearable technology to mobile health apps, all geared to meet the diverse needs of the patient population. ...
The dynamic field of the Internet of Things (IoT) is constantly increasing, providing a plethora of potential integration across various sectors, most notably healthcare. The IoT represents a significant technological leap in healthcare management systems, coinciding with the rising preference for personalized, proactive, cost-effective treatment techniques. This review aimed to thoroughly assess the existing literature through a systematic review and bibliometric analysis, identifying untapped research routes and possible domains for further exploration. The overarching goal was to provide healthcare professionals with significant insights into the impact of IoT technology on Patient Medication Adherence (PMA) and related outcomes. An extensive review of 314 scientific articles on the deployment of IoT within pharmaceutical care services revealed a rising trend in publication volume, with a significant increase in recent years. Pertinently, from the 33 publications finally selected, substantial data support the potential of the IoT to improve PMA, particularly among senior patients with chronic conditions. This paper also comments on various regularly implemented IoT-based systems, noting their unique benefits and limitations. In conclusion, the critical relevance of PMA is highlighted, arguing for its emphasis in future discussions. Furthermore, the need for additional research endeavors is proposed to face and overcome existing constraints and establish the long-term effectiveness of IoT technologies in maximizing patient outcomes.
The term internet of things (IoT) denotes the advanced phase of the internet, wherein a worldwide communication infrastructure is established between individuals and machines. The IoT is now being developed as a worldwide infrastructure that has the potential to significantly transform various aspects of human life. Nevertheless, the interconnected nature of IoT systems and the involvement of other disciplines in their implementation have presented novel security obstacles. However, the utilization of deep learning techniques holds significant importance in enhancing the security of IoT systems. This transformation goes beyond the facilitation of secure communication between devices, as it enables the development of intelligent systems that prioritize security. In this chapter, the basic architecture of IoT has been discussed with its applications and security challenges. Different deep-learning techniques for securing IoT devices with their strengths and weaknesses have also been explored.
Internet of Things (IoT) is a modern technology that has significantly improved efficiency and deployment of medical devices in healthcare sector. Various approaches have been presented in the literature for integrating IoT with medical devices to solve various healthcare problems and overcome the potential challenges in conventional approaches, such as enhancing device’s operational efficiency, reducing implementational costs, and improving both access and patient’s safety. This paper highlights different implementation approaches based on both business and technical goals which are considered very important steps and strategy analysis in developing IoT medical devices. These goals enable the developers during planning phase to select the appropriate standards. This is because there are many different industry standards that can be adopted for integrating IoT with medical devices as discussed in this paper, e.g., communication standards for connectivity, artificial intelligence algorithms for data analysis, and cloud computing have various implementation requirements. Finally, the networking technical goals of IoT are discussed for specifying the reliability and efficiency of the developed IoT approach.
Medical Internet of Things, also well known as MIoT, is playing a more and more important role in improving the health, safety, and care of billions of people after its showing up. Instead of going to the hospital for help, patients’ health-related parameters can be monitored remotely, continuously, and in real time, then processed, and transferred to medical data center, such as cloud storage, which greatly increases the efficiency, convenience, and cost performance of healthcare. The amount of data handled by MIoT devices grows exponentially, which means higher exposure of sensitive data. The security and privacy of the data collected from MIoT devices, either during their transmission to a cloud or while stored in a cloud, are major unsolved concerns. This paper focuses on the security and privacy requirements related to data flow in MIoT. In addition, we make in-depth study on the existing solutions to security and privacy issues, together with the open challenges and research issues for future work.
This paper presents a system consisting of a smart medicine dispenser of solid medications (pills, capsules,.. .) and a mobile application for its configuration and management. The main idea is to offer a solution to help people (es-pecially vulnerable ones) to avoid incorrect medication intakes. In this regard, the smart dispenser delivers the required medication if two conditions are met: (1) it is the scheduled time for a medication intake, and (2) the person who removes the medication from the dispenser (patient or caregiver) can be identified and is authorized to do so. Person identification and authorization is performed through facial recognition by the dispenser and through a username and a password by the mobile application. Moreover, the system reminds the users whenever a medication intake should take place through mobile notifications and lights and sounds emitted by the dispenser. The system development has been guided by a Test-Driven Development Methodology for Internet of Things (IoT)-based Systems to promote its quality and reliability.
Online health communities generally provide a
platform for patients and their families to learn about an illness,
seek and suggest support, and connect with other peers in
analogous situations. In this paper, an architecture and
implementation of an automatic medicine dispenser is proposed
to support and extend the online health communities. Through
this solution, doctor in the online health community may suggest
pills based on the health conditions of their patients as
communicated by them through online platform. Each user is
secured with a unique barcode while starting the communication
between the doctor and the patient. The barcode may then be
scanned in the nearby automatic pill dispenser that can dispatch
the medicine. Cloud is used as a medium to support Storage as a
Service. The proposed model eliminates the need to spend time to
visit the doctor and the time to spend in pharmacy. Also, the
patients are relieved from the errors that might be caused due to
handwriting misinterpretation and change of medicine that exists
in manual medicine dispensing system.
Objective: To describe pill burden before and after hepatitis C virus (HCV) treatment initiation among patients newly treated for HCV infection, and to evaluate the association between HCV pill burden and gaps in HCV therapy.
Methods: This was a retrospective administrative claims study of patients treated with direct-acting antivirals (DAAs) for HCV from 01 November 2013 – 31 July 2016. HCV pill burden was defined as the pill count per day for the index HCV regimen. Mean overall pill burden (HCV medications plus non-HCV medications) was calculated in the 90 days before and after DAA initiation. Gaps in the index HCV regimen were assessed in the 6 months after DAA initiation. Multivariable logistic regression was used to compare the odds of a gap in HCV therapy across HCV pill burden categories (1 pill/day, 2 pills/day, and ≥3 pills/day).
Results: Among 9,815 patients who met the study criteria, mean overall pill burdens before and after DAA treatment initiation were 5.4 and 7.7, respectively (p < 0.001). The adjusted odds ratio (OR) of a ≥ 15-day gap in HCV therapy was 1.75 (95% confidence interval [CI] = 1.38-2.22) for patients with 2 HCV pills/day and 2.11 (95% CI =1.78-2.51) for patients with ≥3 pills/day, compared with patients with 1 HCV pill/day.
Conclusions: Patients with HCV have a substantial pill burden even before initiating HCV treatment. As higher HCV pill burden was associated with lower medication adherence, pill burden should be an important consideration in HCV treatment selection.
Many medical errors are due to the fact that people in charge of patient or elder's medication have to deal with sorting huge amounts of pills each day. This paper consists on the conception, design and creation of a pillbox prototype intended to solve this deficiency in the medical area as it has the ability of sorting out the pills by itself as well as many other advanced features, with this device being intended to be used by hospitals or retirement homes. This medication pill box is focused on patients who frequently take medications or vitamin supplements, or attendants who deal with the more seasoned or patients. Our smart pill box is programmable that enables medical caretakers or clients to determine the pill amount and timing to take pills, and the service times for every day. Our shrewd pills box contains nine separate sub-boxes. In this manner, medical caretakers or clients can set data for nine distinct pills. At the point when the pill time has been set, the pillbox will remind clients or patients to take pills utilizing sound and light. The warning of pills should be taken will be shown by an android application which is held by the patient. Contrasted and the conventional pill box that requires clients or attendants to stack the crate each day or consistently. Our shrewd pill box would essentially discharge medical attendants or clients' weight on much of the time preloading pills for patients or clients and overlook the measurements which must be taken. Keywords: Smart Pill box, IoT, Health Care, Medicine Reminder
Introduction: The geriatric population of the world is increasing, who very often suffers from multiple comorbidities and exposed to polypharmacy by multiple treating physicians. Aim: The study attempts to understand the challenges of pharmacotherapy in the elderly and to explore if expert oversight could address such problem optimally. Materials and Methods: A prospective, randomized, observational and interventional community based study was conducted for a year on 75 elderly subjects (>60 years) of either sex in a specific semi urban community who were randomly divided into supervised (n=40) and unsupervised (n=35) groups. The supervised group received professional counselling and guidance throughout the study period where as the other group were just routinely followed up every two months and data were collected in predesigned and validated questionnaire at each intervention. Results: Knowledge regarding medicines like the dose, frequency, duration of treatment etc., was limited across the study subjects. The impact of supervision on medication adherence was evident in the supervised group (p <0.0001). Inappropriate medication was found in almost one third of study subjects with no significant impact of professional supervision. Compliance was a very big challenge across all the elderly subjects and the most common cause for not taking medicines at regular basis was forgetfulness (41.33%) followed by inconvenience of some sort in taking medicines (13.34%) which remained unaffected by supervision. Conclusion: Communication between patient and health care provider has a significant role to play though limited for medication use and its management among the elderly subjects. Continuous monitoring by professional experts can exert a positive impact on the quality of health of the elderly population. © 2018, Journal of Clinical and Diagnostic Research. All rights reserved.
With the latest research in the fields of medicine and pharmaceutical sciences, an increasing number of drugs are being invented to cure many fatal diseases and this has enabled people to live healthier and longer. Consequently, the rate of medication usage is increasing, particularly among the elderly. It is important that the medication prescribed by doctors is taken at the correct times of the day and in the correct dosages. This seems to be a significant problem encountered by older people with disabilities. As a result of forgetfulness or other problems, many older patients either do not take the correct medicines or the correct dosage at the appropriate times and this reduces the benefits of treatments and increases both healthcare costs and the mortality rates. In order to find a solution to this problem, a mobile phone and Cloud-based smart application has been developed to improve patient adherence, particularly for older people with disabilities. The novelty of the developed application is the use of a Cloud service to provide two-way communication in the form of feedback between the older patients with disabilities and the doctors so that the medication adherence of the patients can be monitored. Mobile application developers should find the developed mobile phone based medication reminder application for older people with disabilities a useful example application, and it should help them in developing other mobile applications for older people with disabilities.
Introduction: Non-adherence to medication is present in ≥50% of patients with apparent treatment resistant hypertension1. We examined the factors associated with non-adherence detected by LC-MS/MS based urine antihypertensive drug assay2,
Methods: All urine antihypertensive test results, done for uncontrolled hypertension (BP persistently >140/90 mmHg) between January 2015 and December 2016 at Heartlands Hospital toxicology laboratory, were analysed. Drugs detected were compared to the antihypertensive drugs prescribed. Patients were classified as adherent (all drugs detected), partially adherent (≥1 prescribed drugs detected) or non-adherent (no drugs detected). Demographic and clinical data were compared across the 3 groups (Table).
Results: 335 clinical samples from 9 hypertension centres across the UK were received for analysis during the timeframe. Significant results are shown in Table.
Adherent Partially Adherent Non-adherent p
No of Patients (%) 139 (43.2) 123 (38.2) 60 (18.6) -
% Female 38 49 68 -
Age 64 (19) 56 (17)** 53 (16)** <0.001
Antihypertensive Drugs Prescribed 4 (1) 4 (3)* 5 (2)** <0.001
Total Drugs Prescribed 5 (3) 7 (5)* 7 (4)** <0.001
BP Systolic (mmHg) 172 (30) 177 (41) 185 (31)* 0.027
BP Diastolic (mmHg) 90 (27) 98 (30)* 106 (24)** <0.001
eGFR (mL/min/1.73m2) 63 (26) 71 (28) 76 (17)* 0.005
Conclusions: Non-adherence to antihypertensive medication was associated with total pill burden, number of antihypertensives prescribed, lower age, female gender, higher blood pressure and higher eGFR.
References:
1. Hameed A, Dasgupta I and Gill PS. BMJ 2016; 354 doi: http://dx.doi.org/10.1136/bmj.i3268
2. Lawson AJ,.. Dasgupta I. J Anal Toxicol. 2016 Jan;40(1):17-27
Internet of Things (IoT) offers a seamless platform to connect people and objects to one another for enriching and making our lives easier. This vision carries us from compute-based centralized schemes to a more distributed environment offering a vast amount of applications such as smart wearables, smart home, smart mobility, and smart cities. In this paper we discuss applicability of IoT in healthcare and medicine by presenting a holistic architecture of IoT eHealth ecosystem. Healthcare is becoming increasingly difficult to manage due to insufficient and less effective healthcare services to meet the increasing demands of rising aging population with chronic diseases. We propose that this requires a transition from the clinic-centric treatment to patient-centric healthcare where each agent such as hospital, patient, and services are seamlessly connected to each other. This patient-centric IoT eHealth ecosystem needs a multi-layer architecture: (1) device, (2) fog computing and (3) cloud to empower handling of complex data in terms of its variety, speed, and latency. This fog-driven IoT architecture is followed by various case examples of services and applications that are implemented on those layers. Those examples range from mobile health, assisted living, e-medicine, implants, early warning systems, to population monitoring in smart cities. We then finally address the challenges of IoT eHealth such as data management, scalability, regulations, interoperability, device-network-human interfaces, security, and privacy.
Opening and closing processes are those that manipulate the erosion and dilation processes to improve the image. Both processes depend on the characteristics of the structuring element to process the image in order to gain a better image. The opening and closing process were performed on the binary image and the erosion and dilation process was discussed. Then, a different characteristic of the structuring element was used to compare the opening and closing processes' results. As a result, the opening process removed the foreground structures that were smaller than the structuring element, while the closing process removed background structures that were smaller than the structuring element. Then, using different characteristics of the structuring element were found to affect the operations, and also mathematical morphological-image processing. Based on the results, the opening and closing processes improved the image by reducing the noise and the characteristics of the structuring element act as the important probe.
Medication adherence and persistence is recognized as a worldwide public health problem, particularly important in the management of chronic diseases. Nonadherence to medical plans affects every level of the population, but particularly older adults due to the high number of coexisting diseases they are affected by and the consequent polypharmacy. Chronic disease management requires a continuous psychological adaptation and behavioral reorganization. In literature, many interventions to improve medication adherence have been described for different clinical conditions, however, most interventions seem to fail in their aims. Moreover, most interventions associated with adherence improvements are not associated with improvements in other outcomes. Indeed, in the last decades, the degree of nonadherence remained unchanged. In this work, we review the most frequent interventions employed to increase the degree of medication adherence, the measured outcomes, and the improvements achieved, as well as the main limitations of the available studies on adherence, with a particular focus on older persons.
One of the most challenging problems for researchers in the field of image processing is image quality assessment. A very important factor in image quality assessment is image sharpness/blurriness. The goal of researchers in the field of image quality assessment is to design and develop algorithms and measures for detecting sharpness and blurriness in an image. In this paper a new technique is proposed to calculate image sharpness/blurriness measure in frequency domain. (C) 2013 The Authors. Published by Elsevier Ltd.
Potentially inappropriate medication (PIM) prescribing in older adults is quite prevalent and is associated with an increased risk for adverse drug events, morbidity, and utilization of health care resources. In the acute care setting, PIM prescribing can be even more problematic due to multiple physicians and specialists who may be prescribing for a single patient as well as difficulty with medication reconciliation at transitions and limitations imposed by hospital formularies. This article highlights critical issues surrounding PIM prescribing in the acute care setting such as risk factors, screening tools, and potential strategies to minimize this significant public health problem.
Background. Contemporary antiretroviral treatment regimens are simpler than in the past, with lower pill burden and once-daily dosing frequency common. We performed a meta-analysis of randomized controlled trials (RCTs) to investigate the impact of pill burden and once-daily vs twice-daily dosing on ART adherence and virological outcomes.
Methods. A literature search of 4 electronic databases through 31 March 2013 was used. RCTs comparing once-daily vs twice-daily ART regimens that also reported on adherence and virological suppression were included. Study design, study population characteristics, intervention, outcome measures, and study quality were extracted. Study quality was rated using the Cochrane risk-of-bias tool.
Results. Nineteen studies met our inclusion criteria (N = 6312 adult patients). Higher pill burden was associated with both lower adherence rates (P = .004) and worse virological suppression (P < .0001) in both once-daily and twice-daily subgroups, although the association with adherence in the once-daily subgroup was not statistically significant. The average adherence was modestly higher in once-daily regimens than twice-daily regimens (weighted mean difference = 2.55%; 95% confidence interval [CI], 1.23 to 3.87; P = .0002). Patients on once-daily regimens did not achieve virological suppression more frequently than patients on twice-daily regimens (relative risk [RR] = 1.01; 95% CI, 0.99 to 1.03; P = .50). Both adherence and viral load suppression decreased over time, but adherence decreased less with once-daily dosing than with twice-daily dosing.
Conclusions. Lower pill burden was associated with both better adherence and virological suppression. Adherence, but not virological suppression, was slightly better with once- vs twice-daily regimens.
The output from a color imaging sensor, or apparent color, can change considerably due to illumination conditions and scene geometry changes. In this work we take into account the dependence of apparent color with illumination an attempt to find appropriate color models for the typical conditions found in outdoor settings. We evaluate three color based trackers, one based on hue, another based on an intrinsic image representation and the last one based on a proposed combination of a chromaticity model with a physically reasoned adaptation of the target model. The evaluation is done on outdoor sequences with challenging illumination conditions, and shows that the proposed method improves the average track completeness by over 22% over the hue-based tracker and the closeness of track by over 7% over the tracker based on the intrinsic image representation.
The progress in IoT health care is considered to
be a massive contribution to the elderly people. The elderly
people and people who are suffering from chronic diseases
need to intake tablets regularly on timely basis. Care takers
with their busy daily routine may forget the instructions and
time about pills which are prescribed for patient. Also care
takers who are dealing increased number of patients may feel
hectic to sort the medicine list for corresponding patients at
proper time. Earlier many researches have been carried in this
area and different pill boxes have been proposed already. The
intelligent medication box proposed in this work have
specialized features including six sub boxes which helps to
organize six different pills, provides timely remainders for the
patient or caretaker in an android application like hand-held
devices like smartphone. This intelligent medication box
contains bio-sensor for monitoring of temperature and
heartbeat. Overdosage and improper intake of medicines may
lead to serious issues in health of elderly people to avoid mis
usage of medicines a simple authentication process either by
the care taker or the patient himself is performed. The
proposed medication is much safer as it clearly intimates about
time, dosage, stock of medicine and sorts out different pills in
correct sub boxes during the next fill by caretaker
Ensuring optimal medication adherence is a complex problem and require involvement of multiple stakeholders in a healthcare system. Poor medication adherence leads to severe health consequences as well a serious increase in healthcare costs. To address the problem of medication nonadherence, technological solutions which use Medication Event Monitoring Systems (MEMS) combined with in-person interventions have been recommended by researchers. In this paper, we elaborate the architecture of an IoT and blockchain based medication adherence system that uses a newer generation MEMS device developed by Baswen Medication. The system consists of the functionalities for stakeholder registration, device configuration, medication adherence data management and reminder/notification support to increase degree of medication adherence. We justify the advantages of using blockchain technology and report on the progress of system development.
SIMoP Box is a smart healthcare system that can be used in multiple scenarios like patient isolation condition, semi-paralyzed patients, and Patients under medication suffering from mild memory loss conditions. In such cases, this system is equally beneficial for patients as well as caretakers, who may be forced to leave patients at home while busy with work during the whole day. This system will take care of the dispensing of the right dosage of medicines at the right time, using a built-in timer, and reminds patients about the medication by firing an alarm. Along with the medication appropriate amount of water is also provided using a liquid dispenser and the integrated air cooling assembly regulates the temperature in the room. An IP-camera connected to the device offers a remote monitoring facility of the patient on the caretaker’s smartphone.
In recent days, Internet of Things (IoT) pave the way for lot of opportunities in terms of discovery, product and user applications. Based on the IoT, medical sector is moving towards a smarter health-based application to diagnosis, treatment and control of health issues. This chapter will discuss an IoT-based pill dispenser application to provide how proper mediation to the patient can be achieved for a healthier life. The purpose of the proposed dispenser pills is to monitor the proper intake of pills for our self, and especially for elders, which is much more important. IoT is integrated to provide human interaction between the patient and doctor to monitor and provide proper dosage of medication to the patient. By having a wide discussion on the IoT and cloud based on pill dispenser, we have analysed and compared various pill dispensers and how they differ from cloud-based health application.
Neurodegenerative illnesses due to diseases or old age are typical examples of clinical conditions that may affect the proper observation of prescribed medication usage with negative consequence on dose potency. Commercially available medicine dispenser for these populations are expensive, complex to operate and/or beyond the reach of those living in low resource settings due to lack of social protection. This study presents the design and construction of an inexpensive ($49.6) medication dispenser suitable for point of care applications in low resource settings. The dispenser was constructed using a simple control mechanism based on Arduino® IDE that controlled three different micro servo motors to accommodate different shapes of medication. Sequel to the laboratory trials by abled individuals, we were able to demonstrate between 58% and 100% accuracy of the device when the three servo motors were simultaneously used to dispense medication of three different sizes. Following rigorous clinical trials in the target population, we intend to deploy this device for wider and independent usage by users in order to prevent unnecessary hospital admission meant to enforce compliance with appropriate medication usage for the users.
Improving medication adherence may have a greater influence on the health of our population than in the discovery of any new therapy. Patients are nonadherent to their medicine 50% of the time. Although most physicians believe nonadherence is primarily due to lack of access or forgetfulness, nonadherence can often be an intentional choice made by the patient. Patient concealment of their medication-taking behavior is often motivated by emotions on the part of both provider and patient, leading to potentially dire consequences. A review of the literature highlights critical predictors of adherence including trust, communication and empathy, which are not easily measured by current administrative databases. Multifactorial solutions to improve medication adherence include efforts to improve patients’ understanding of medication benefits, access and trust in their provider and health system. Improving providers’ recognition and understanding of patients’ beliefs, fears and values, as well as their own biases is also necessary to achieve increased medication adherence and population health.
Medication adherence is a crucial component in the treatment of chronic diseases. In the elderly, cli- nicians are faced with a unique set of problems associated with adherence that they may not have been adequately trained for. In this paper, we demonstrate the importance of medication adherence in the elderly through a case study. The different factors affecting medication adherence in the elderly are highlighted: patient, medication, health care providers, health care system, and socioeconomic factors. Lastly, we have proposed various ways to address these factors. In doing so, clinicians can better un- derstand the problems that the elderly face, thus achieving better therapeutic outcomes.
IoT based health monitoring and pill dispenser system
- Rajendran