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Background Technological progress has enabled the provision of personalised feedback across multiple dimensions of physical activity that are important for health. Whether this multidimensional approach supports physical activity behaviour change has not yet been examined. Our objective was to examine the effectiveness of a novel digital system and app that provided multidimensional physical activity feedback combined with health trainer support in primary care patients identified as at risk of chronic disease. Methods MIPACT was a parallel-group, randomised controlled trial that recruited patients at medium (≥10 and < 20%) or high (≥20%) risk of cardiovascular disease and/or type II diabetes from six primary care practices in the United Kingdom. Intervention group participants ( n  = 120) received personal multidimensional physical activity feedback using a customised digital system and web-app for 3 months plus five health trainer-led sessions. All participants received standardised information regarding physical activity. Control group participants ( n  = 84) received no further intervention. The primary outcome was device-based assessment of physical activity at 12 months. Results Mean intervention effects were: moderate-vigorous physical activity: -1.1 (95% CI, − 17.9 to 15.7) min/day; moderate-vigorous physical activity in ≥10-min bouts: 0.2 (− 14.2 to 14.6) min/day; Physical Activity Level (PAL): 0.00 (− 0.036 to 0.054); vigorous physical activity: 1.8 (− 0.8 to 4.2) min/day; and sedentary time: 10 (− 19.3 to 39.3) min/day. For all of these outcomes, the results showed that the groups were practically equivalent and statistically ruled out meaningful positive or negative effects (>minimum clinically important difference, MCID). However, there was profound physical activity multidimensionality, and only a small proportion (5%) of patients had consistently low physical activity across all dimensions. Conclusion In patients at risk of cardiovascular disease and/or type II diabetes, MIPACT did not increase mean physical activity. Using a sophisticated multidimensional digital approach revealed enormous heterogeneity in baseline physical activity in primary care patients, and practitioners may need to screen for low physical activity across dimensions rather than rely on disease-risk algorithms that are heavily influenced by age. Trial registration This trial is registered with the ISRCTN registry ( ISRCTN18008011 ; registration date 31 July 2013).

Objectives The aim of this study was to evaluate the effects of an mHealth intervention (intervention using mobile technology) consisting of tailored advice regarding exposure to daylight, sleep, physical activity, and nutrition, and aiming to improve health-related behavior, thereby reducing sleep problems and fatigue and improving health perception of airline pilots. Methods A randomized controlled trial was conducted among 502 airline pilots. The intervention group was given access to both the MORE Energy mobile application (app) with tailored advice and a website with background information. The control group was directed to a website with standard information about fatigue. Healthrelated behavior, fatigue, sleep, and health perception outcomes were measured through online questionnaires at baseline and at three and six months after baseline. The effectiveness of the intervention was determined using linear and Poisson mixed model analyses. Results After six months, compared to the control group, the intervention group showed a significant improvement on fatigue (β= -3.76, P<0.001), sleep quality (β= -0.59, P=0.007), strenuous physical activity (β= 0.17, P=0.028), and snacking behavior (β= -0.81, P<0.001). No significant effects were found for other outcome measures. Conclusions The MORE Energy mHealth intervention reduced self-reported fatigue compared to a minimal intervention. Some aspects of health-related behavior (physical activity and snacking behavior) and sleep (sleep quality) improved as well, but most did not. The results show offering tailored advice through an mHealth intervention is an effective means to support employees who have to cope with irregular flight schedules and circadian disruption. This kind of intervention might therefore also be beneficial for other working populations with irregular working hours.

Deep brain stimulation (DBS) is a neurosurgical procedure that allows targeted circuit-based neuromodulation. DBS is a standard of care in Parkinson disease, essential tremor and dystonia, and is also under active investigation for other conditions linked to pathological circuitry, including major depressive disorder and Alzheimer disease. Modern DBS systems, borrowed from the cardiac field, consist of an intracranial electrode, an extension wire and a pulse generator, and have evolved slowly over the past two decades. Advances in engineering and imaging along with an improved understanding of brain disorders are poised to reshape how DBS is viewed and delivered to patients. Breakthroughs in electrode and battery designs, stimulation paradigms, closed-loop and on-demand stimulation, and sensing technologies are expected to enhance the efficacy and tolerability of DBS. In this Review, we provide a comprehensive overview of the technical development of DBS, from its origins to its future. Understanding the evolution of DBS technology helps put the currently available systems in perspective and allows us to predict the next major technological advances and hurdles in the field.Deep brain stimulation (DBS) is a neurosurgical procedure that allows targeted circuit-based neuromodulation and has become a standard of care in a range of movement disorders. This Review discusses the evolution and current status of DBS technology and anticipates future advances.

One of the most popular methods to fabricate biomedical microfluidic devices is by using a soft-lithography technique. However, the fabrication of the moulds to produce microfluidic devices, such as SU-8 moulds, usually requires a cleanroom environment that can be quite costly. Therefore, many efforts have been made to develop low-cost alternatives for the fabrication of microstructures, avoiding the use of cleanroom facilities. Recently, low-cost techniques without cleanroom facilities that feature aspect ratios more than 20, for fabricating those SU-8 moulds have been gaining popularity among biomedical research community. In those techniques, Ultraviolet (UV) exposure equipment, commonly used in the Printed Circuit Board (PCB) industry, replaces the more expensive and less available Mask Aligner that has been used in the last 15 years for SU-8 patterning. Alternatively, non-lithographic low-cost techniques, due to their ability for large-scale production, have increased the interest of the industrial and research community to develop simple, rapid and low-cost microfluidic structures. These alternative techniques include Print and Peel methods (PAP), laserjet, solid ink, cutting plotters or micromilling, that use equipment available in almost all laboratories and offices. An example is the xurography technique that uses a cutting plotter machine and adhesive vinyl films to generate the master moulds to fabricate microfluidic channels. In this review, we present a selection of the most recent lithographic and non-lithographic low-cost techniques to fabricate microfluidic structures, focused on the features and limitations of each technique. Only microfabrication methods that do not require the use of cleanrooms are considered. Additionally, potential applications of these microfluidic devices in biomedical engineering are presented with some illustrative examples.

Electronics are set to merge with our bodies to extend our perceptions. Smartphones and watches will give way to the bodyNET1: a network of sensors, screens and smart devices woven into our clothing, worn on our skin and implanted in our bodies (see 'Superhuman powers').

Wearable potentiometric sensors have received considerable attention owing to their great potential in a wide range of physiological and clinical applications, particularly involving ion detection in sweat. Despite the significant progress in the manner that potentiometric sensors are integrated in wearable devices, in terms of materials and fabrication approaches, there is yet plenty of room for improvement in the strategy adopted for the sample collection. Essentially, this involves a fluidic sampling cell for continuous sweat analysis during sport performance or sweat accumulation via iontophoresis induction for one-spot measurements in medical settings. Even though the majority of the reported papers from the last five years describe on-body tests of wearable potentiometric sensors while the individual is practicing a physical activity, the medical utilization of these devices has been demonstrated on very few occasions and only in the context of cystic fibrosis diagnosis. In this sense, it may be important to explore the implementation of wearable potentiometric sensors into the analysis of other biofluids, such as saliva, tears and urine, as herein discussed. While the fabrication and uses of wearable potentiometric sensors vary widely, there are many common issues related to the analytical characterization of such devices that must be consciously addressed, especially in terms of sensor calibration and the validation of on-body measurements. After the assessment of key wearable potentiometric sensors reported over the last five years, with particular attention paid to those for medical applications, the present review offers tentative guidance regarding the characterization of analytical performance as well as analytical and clinical validations, thereby aiming at generating debate in the scientific community to allow for the establishment of well-conceived protocols.

Endovascular treatment of intracranial aneurysms (IAs) has evolved considerably over the past decades. The technological advances have been driven by the experience that coils fail to completely exclude all IAs from the blood circulation, the need to treat the diseased parent vessel segment leading to the aneurysm formation, and expansion of endovascular therapy to treat more complex IAs. Stents were initially developed to support the placement of coils inside wide neck aneurysms. However, early work on stent-like tubular braided structure led to a more sophisticated construct that then later was coined as a flow diverter (FD) and found its way into clinical application. Although FDs were initially used to treat wide-neck large and giant internal carotid artery aneurysms only amenable to surgical trap with or without a bypass or endovascular vessel sacrifice, its use in other types of IAs and cerebrovascular pathology promptly followed. Lately, we have witnessed an explosion in the application of FDs and subsequently their modifications leading to their ubiquitous use in endovascular therapy. In this review we aim to compile the available FD technology, evaluate the devices’ peculiarities from the authors’ perspective, and analyze the current literature to support initial and expanded indications, recognizing that this may be outdated soon.

The past decade in rheumatology has seen tremendous innovation in digital health technologies, including the electronic health record, virtual visits, mobile health, wearable technology, digital therapeutics, artificial intelligence and machine learning. The increased availability of these technologies offers opportunities for improving important aspects of rheumatology, including access, outcomes, adherence and research. However, despite its growth in some areas, particularly with non-health-care consumers, digital health technology has not substantially changed the delivery of rheumatology care. This Review discusses key barriers and opportunities to improve application of digital health technologies in rheumatology. Key topics include smart design, voice enablement and the integration of electronic patient-reported outcomes. Smart design involves active engagement with the end users of the technologies, including patients and clinicians through focus groups, user testing sessions and prototype review. Voice enablement using voice assistants could be critical for enabling patients with hand arthritis to effectively use smartphone apps and might facilitate patient engagement with many technologies. Tracking many rheumatic diseases requires frequent monitoring of patient-reported outcomes. Current practice only collects this information sporadically, and rarely between visits. Digital health technology could enable patient-reported outcomes to inform appropriate timing of face-to-face visits and enable improved application of treat-to-target strategies. However, best practice standards for digital health technologies do not yet exist. To achieve the potential of digital health technology in rheumatology, rheumatology professionals will need to be more engaged upstream in the technology design process and provide leadership to effectively incorporate the new tools into clinical care.Digital health technologies (DHTs) have a variety of interesting current and possible future applications in rheumatology. In this article, the authors describe some of the key barriers that prevent DHT integration into rheumatology care and discuss ways in which these barriers could be addressed.

Background Falls are a major health problem for older adults with significant physical and psychological consequences. A first step of successful fall prevention is to identify those at risk of falling. Recent advancement in sensing technology offers the possibility of objective, low-cost and easy-to-implement fall risk assessment. The objective of this systematic review is to assess the current state of sensing technology on providing objective fall risk assessment in older adults. Methods A systematic review was conducted in accordance to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement (PRISMA). Results Twenty-two studies out of 855 articles were systematically identified and included in this review. Pertinent methodological features (sensing technique, assessment activities, outcome variables, and fall discrimination/prediction models) were extracted from each article. Four major sensing technologies (inertial sensors, video/depth camera, pressure sensing platform and laser sensing) were reported to provide accurate fall risk diagnostic in older adults. Steady state walking, static/dynamic balance, and functional mobility were used as the assessment activity. A diverse range of diagnostic accuracy across studies (47.9% - 100%) were reported, due to variation in measured kinematic/kinetic parameters and modelling techniques. Conclusions A wide range of sensor technologies have been utilized in fall risk assessment in older adults. Overall, these devices have the potential to provide an accurate, inexpensive, and easy-to-implement fall risk assessment. However, the variation in measured parameters, assessment tools, sensor sites, movement tasks, and modelling techniques, precludes a firm conclusion on their ability to predict future falls. Future work is needed to determine a clinical meaningful and easy to interpret fall risk diagnosis utilizing sensing technology. Additionally, the gap between functional evaluation and user experience to technology should be addressed.

Wearable medical devices (WMDs) will advance point-of-care diagnostics and therapeutics. This article analyses the market and patents for wearable devices. Activity monitors have the largest market share, and the intellectual property landscape is dominated by electronics corporations. However, the majority of these patents have not been realized in commercial products.