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Although external fixation is being widely used by orthopedic surgeons in the treatment of bone fractures, the surgical procedure and recovery are still followed by a number of possible complications which can significantly decrease the treatment’s efficiency (cost) and effectiveness (optimal healing). Inability of the physician to have continuous...
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... gateway is capable to receive and collect data from the sensors, to process this data and make conclusions and to act based on those conclusions by controlling corresponding actuators, or by messaging capability. The gateway can be accessed to input or to manipulate patient data; it is also connected to Clinical Information System (CIS), with which it can interoperate (see Figure 2). ...
Citations
... In orthopaedics first ever classification by Misic., et al. (2018) described four types of IOT based external fixation devices [28]. Type 1 tagging system to resolve logistics problems, type 2 sensing system to collect physiological or environmental data, type 3 an intelligent system that can make sense of combined data from different sources, and type 4 is a closed-loop system that senses, makes intelligent decisions, and drives an actuator accordingly [28]. ...
... In orthopaedics first ever classification by Misic., et al. (2018) described four types of IOT based external fixation devices [28]. Type 1 tagging system to resolve logistics problems, type 2 sensing system to collect physiological or environmental data, type 3 an intelligent system that can make sense of combined data from different sources, and type 4 is a closed-loop system that senses, makes intelligent decisions, and drives an actuator accordingly [28]. ...
The increasing use of IoT in the medical field necessitates the adoption of specialized terminology, such as the "Internet of Or-thopedic Things (IOT)" to accurately describe and distinguish this specific area of application. The IOT is a rapidly growing field that combines orthopedic devices with internet connectivity and data analytics. This review paper provides an overview of the IOT, including its definition, components, and applications in orthopedic healthcare with special focus on its classification. The IOT has the potential to revolutionize the way orthopedic healthcare is delivered by providing real-time monitoring, personalized treatment, and remote care. Different IOT devices, including smart implants, wearable sensors, and mobile applications, and their use in orthopedic diagnosis, treatment, and rehabilitation have been discussed. It aims to serve as a valuable resource for healthcare professionals, researchers, and policymakers seeking to gain insight into the IOT and its potential impact on orthopedic healthcare.
... is article proposes a training target-oriented RGB colour separation of background difference target detection, which improves the effectiveness of the colour separation method. e concept of the training target monitoring system is to accurately segment and extract the training targets in the monitoring area by setting up a monitoring camera above the training targets and count their number and area for subsequent tracking and recognition processing, regardless of whether the area needs cleanup judgment or decisionmaking [17,18]. e hardware components of the system include network cameras, routers, display terminals, storage servers, and other equipment to complete video collection, transmission, data processing, distribution, decision-making and execution, and archiving. ...
The detection of moving targets is to detect the change area in a sequence of images and extract the moving targets from the background image. It is the basis. Whether the moving targets can be correctly detected and segmented has a huge impact on the subsequent work. Aiming at the problem of high failure rate in the detection of sports targets under complex backgrounds, this paper proposes a research on the design of an intelligent background differential model for training target monitoring. This paper proposes a background difference method based on RGB colour separation. The colour image is separated into independent RGB three-channel images, and the corresponding channels are subjected to the background difference operation to obtain the foreground image of each channel. In order to retain the difference of each channel, the information of the foreground images of the three channels is fused to obtain a complete foreground image. The feature of the edge detection is not affected by light; the foreground image is corrected. From the experimental results, the ordinary background difference method uses grey value processing, and some parts of the target with different colours but similar grey levels to the background cannot be extracted. However, the method in this paper can better solve the defect of misdetection. At the same time, compared with traditional methods, it also has a higher detection efficiency.
... Technically, an ASSA system is achieved by embedding sensors to the devices connected to a processing unit that collects, stores, processes and classifies data in order to derive conclusions based on these sensor signals. Dragan et al. [17] developed an ASSA systemto be used for monitoring the load applied on fractured leg by the mounted load cell and recognizing patient's high risk activity that may hinder the healing process. Both problems were represented as a classification problems.They found that using a single accelerometer of high quality placed on the calf, 11 features represing acceleration magnitude, and k-nearest neighbour classification algorithm resulted in the most accurate human activity recognition (96.46%) compared to any other number of selected features or classification algorithms. ...
Bones provide structural aid to the frame, and bone fracture recuperation is crucial for regaining functionality and mobility. The boundaries of traditional external fixators in bone fracture remedy, characterized by a loss of actual-time monitoring and capability complications, necessitate a paradigm shift. To clear up this trouble, a clever fixator design imbued with the transformative energy of Aware, Sensing, Smart, and Active (ASSA) technology has been developed. This fixator transcends its passive role, evolving into a wise IoT gateway. It continuously gathers and analyses facts from numerous incorporated sensors, supplying real-time insights into the tricky dance of fracture healing. Its analytical prowess fosters computerized identification of vital activities and milestones within the affected person's recuperation journey, empowering well-timed interventions and knowledgeable scientific selection-making. Furthermore, the fixator vigilantly monitors patient compliance, making sure adherence to prescribed behaviours and nipping non-compliance in the bud. However, its innovation extends beyond mere monitoring. Embedded within its smart framework lies a modern pain manipulation mechanism powered through a thermoelectric generator (TEG).
The musculoskeletal system, constituting the largest human physiological system, plays a critical role in providing structural support to the body, facilitating intricate movements, and safeguarding internal organs. By virtue of advancements in revolutionized materials and devices, particularly in the realms of motion capture, health monitoring, and postoperative rehabilitation, “musculoskeletal electronics” has actually emerged as an infancy area, but has not yet been explicitly proposed. In this review, the concept of musculoskeletal electronics is elucidated, and the evolution history, representative progress, and key strategies of the involved materials and state‐of‐the‐art devices are summarized. Therefore, the fundamentals of musculoskeletal electronics and key functionality categories are introduced. Subsequently, recent advances in musculoskeletal electronics are presented from the perspectives of “in vitro” to “in vivo” signal detection, interactive modulation, and therapeutic interventions for healing and recovery. Additionally, nine strategy avenues for the development of advanced musculoskeletal electronic materials and devices are proposed. Finally, concise summaries and perspectives are proposed to highlight the directions that deserve focused attention in this booming field.
Transport is one of the largest emitters of harmful
substances that affect air quality. Each transport mode has
different volume of passenger transport and at the same time
has a differentiated negative impact on air quality. That is
why in the European Union has been making special efforts
for many years to create and implement strategies aimed at
improving air quality. The main goal of this paper is to
present a methodology that enables quantification and
analysis of the impacts of each passenger transport mode on
air quality using feed-forward neural networks. The
developed model uses parameters for EU member states in
the period from 2000 to 2014. In addition to the scientific and
practical contribution, the development of model provides a
good basic for the universal platform formation in order to
create and develop strategies, i.e. measures to improve air
quality on global level.
Medicine in general is quickly transitioning to a digital presence. Orthopaedic surgery is also being impacted by the tenets of digital health but there are also direct efforts with trauma surgery. Sensors are the pen and paper of the next wave of data acquisition. Orthopaedic trauma can and will be part of this new wave of medicine. Early sensor products that are now coming to market, or are in early development, will directly change the way we think about surgical diagnosis and outcomes. Sensor development for biometrics is already here. Wellness devices, pressure, temperature, and other parameters are already being measured. Data acquisition and analysis is going to be a fruitful addition to our research armamentarium with the volume of information now available. A combination of broadband internet, micro electrical machine systems (MEMS), and new wireless communication standards is driving this new wave of medicine. The Internet of Things (IoT)(1) now has a subset which is the Internet of Medical Devices ([2], [3], [4], [5])- permitting a much more in-depth dive into patient procedures and outcomes. IoT devices are now being used to enable remote health monitoring, in hospital treatment, and guide therapies. This article reviews current sensor technology that looks to impact trauma care.
A personalized approach in the treatment of patients has always been the aspiration of orthopedists. The degree of personalization was, and still is, limited by the orthopedic methods, devices, and tools available at the time the patient was treated. In the last thirty years, there has been a strong development of new devices and technologies that have enabled a much more personalized approach in the treatment of orthopedic patients. Because these technologies, which are mostly engineering technologies, enable personalized orthopedics, they are called enabling technologies. In this chapter, the concept of personalized orthopedics is first defined, and then the enabling technologies that contribute the most to the practice of personalized orthopedics are identified and described. For each of the enabling technologies, some typical examples of application in personalized orthopedics are given.
