@Article{info:doi/10.2196/50035,
author="Kluge, Felix
and Brand, E. Yonatan
and Mic{\'o}-Amigo, Encarna M.
and Bertuletti, Stefano
and D'Ascanio, Ilaria
and Gazit, Eran
and Bonci, Tecla
and Kirk, Cameron
and K{\"u}derle, Arne
and Palmerini, Luca
and Paraschiv-Ionescu, Anisoara
and Salis, Francesca
and Soltani, Abolfazl
and Ullrich, Martin
and Alcock, Lisa
and Aminian, Kamiar
and Becker, Clemens
and Brown, Philip
and Buekers, Joren
and Carsin, Anne-Elie
and Caruso, Marco
and Caulfield, Brian
and Cereatti, Andrea
and Chiari, Lorenzo
and Echevarria, Carlos
and Eskofier, Bjoern
and Evers, Jordi
and Garcia-Aymerich, Judith
and Hache, Tilo
and Hansen, Clint
and Hausdorff, M. Jeffrey
and Hiden, Hugo
and Hume, Emily
and Keogh, Alison
and Koch, Sarah
and Maetzler, Walter
and Megaritis, Dimitrios
and Niessen, Martijn
and Perlman, Or
and Schwickert, Lars
and Scott, Kirsty
and Sharrack, Basil
and Singleton, David
and Vereijken, Beatrix
and Vogiatzis, Ioannis
and Yarnall, Alison
and Rochester, Lynn
and Mazz{\`a}, Claudia
and Del Din, Silvia
and Mueller, Arne",
title="Real-World Gait Detection Using a Wrist-Worn Inertial Sensor: Validation Study",
journal="JMIR Form Res",
year="2024",
month="May",
day="1",
volume="8",
pages="e50035",
keywords="digital mobility outcomes",
keywords="validation",
keywords="wearable sensor",
keywords="walking",
keywords="digital health",
keywords="inertial measurement unit",
keywords="accelerometer",
keywords="Mobilise-D",
abstract="Background: Wrist-worn inertial sensors are used in digital health for evaluating mobility in real-world environments. Preceding the estimation of spatiotemporal gait parameters within long-term recordings, gait detection is an important step to identify regions of interest where gait occurs, which requires robust algorithms due to the complexity of arm movements. While algorithms exist for other sensor positions, a comparative validation of algorithms applied to the wrist position on real-world data sets across different disease populations is missing. Furthermore, gait detection performance differences between the wrist and lower back position have not yet been explored but could yield valuable information regarding sensor position choice in clinical studies. Objective: The aim of this study was to validate gait sequence (GS) detection algorithms developed for the wrist position against reference data acquired in a real-world context. In addition, this study aimed to compare the performance of algorithms applied to the wrist position to those applied to lower back--worn inertial sensors. Methods: Participants with Parkinson disease, multiple sclerosis, proximal femoral fracture (hip fracture recovery), chronic obstructive pulmonary disease, and congestive heart failure and healthy older adults (N=83) were monitored for 2.5 hours in the real-world using inertial sensors on the wrist, lower back, and feet including pressure insoles and infrared distance sensors as reference. In total, 10 algorithms for wrist-based gait detection were validated against a multisensor reference system and compared to gait detection performance using lower back--worn inertial sensors. Results: The best-performing GS detection algorithm for the wrist showed a mean (per disease group) sensitivity ranging between 0.55 (SD 0.29) and 0.81 (SD 0.09) and a mean (per disease group) specificity ranging between 0.95 (SD 0.06) and 0.98 (SD 0.02). The mean relative absolute error of estimated walking time ranged between 8.9\% (SD 7.1\%) and 32.7\% (SD 19.2\%) per disease group for this algorithm as compared to the reference system. Gait detection performance from the best algorithm applied to the wrist inertial sensors was lower than for the best algorithms applied to the lower back, which yielded mean sensitivity between 0.71 (SD 0.12) and 0.91 (SD 0.04), mean specificity between 0.96 (SD 0.03) and 0.99 (SD 0.01), and a mean relative absolute error of estimated walking time between 6.3\% (SD 5.4\%) and 23.5\% (SD 13\%). Performance was lower in disease groups with major gait impairments (eg, patients recovering from hip fracture) and for patients using bilateral walking aids. Conclusions: Algorithms applied to the wrist position can detect GSs with high performance in real-world environments. Those periods of interest in real-world recordings can facilitate gait parameter extraction and allow the quantification of gait duration distribution in everyday life. Our findings allow taking informed decisions on alternative positions for gait recording in clinical studies and public health. Trial Registration: ISRCTN Registry 12246987; https://www.isrctn.com/ISRCTN12246987 International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2021-050785 ",
doi="10.2196/50035",
url="https://formative.jmir.org/2024/1/e50035",
url="http://www.ncbi.nlm.nih.gov/pubmed/38691395"
}


@Article{info:doi/10.2196/35178,
author="Brobbin, Eileen
and Deluca, Paolo
and Hemrage, Sofia
and Drummond, Colin",
title="Accuracy of Wearable Transdermal Alcohol Sensors: Systematic Review",
journal="J Med Internet Res",
year="2022",
month="Apr",
day="14",
volume="24",
number="4",
pages="e35178",
keywords="alcohol consumption",
keywords="alcohol detection",
keywords="alcohol monitoring",
keywords="alcohol treatment",
keywords="digital technology",
keywords="ecologic momentary assessment",
keywords="transdermal alcohol sensors",
keywords="wearables",
keywords="mobile phone",
abstract="Background: There are a range of wearable transdermal alcohol sensors that are available and are being developed. These devices have the potential to monitor alcohol consumption continuously over extended periods in an objective manner, overcoming some of the limitations of other alcohol measurement methods (blood, breath, and urine). Objective: The objective of our systematic review was to assess wearable transdermal alcohol sensor accuracy. Methods: A systematic search of the CINAHL, Embase, Google Scholar, MEDLINE, PsycINFO, PubMed, and Scopus bibliographic databases was conducted in February 2021. In total, 2 team members (EB and SH) independently screened studies for inclusion, extracted data, and assessed the risk of bias. The methodological quality of each study was appraised using the Mixed Methods Appraisal Tool. The primary outcome was transdermal alcohol sensor accuracy. The data were presented as a narrative synthesis. Results: We identified and analyzed 32 studies. Study designs included laboratory, ambulatory, and mixed designs, as well as randomized controlled trials; the length of time for which the device was worn ranged from days to weeks; and the analyzed sample sizes ranged from 1 to 250. The results for transdermal alcohol concentration data from various transdermal alcohol sensors were generally found to positively correlate with breath alcohol concentration, blood alcohol concentration, and self-report (moderate to large correlations). However, there were some discrepancies between study reports; for example, WrisTAS sensitivity ranged from 24\% to 85.6\%, and specificity ranged from 67.5\% to 92.94\%. Higher malfunctions were reported with the BACtrack prototype (16\%-38\%) and WrisTAS (8\%) than with SCRAM (2\%); however, the former devices also reported a reduced time lag for peak transdermal alcohol concentration values when compared with SCRAM. It was also found that many companies were developing new models of wearable transdermal alcohol sensors. Conclusions: As shown, there is a lack of consistency in the studies on wearable transdermal alcohol sensor accuracy regarding study procedures and analyses of findings, thus making it difficult to draw direct comparisons between them. This needs to be considered in future research, and there needs to be an increase in studies directly comparing different transdermal alcohol sensors. There is also a lack of research investigating the accuracy of transdermal alcohol sensors as a tool for monitoring alcohol consumption in clinical populations and use over extended periods. Although there is some preliminary evidence suggesting the accuracy of these devices, this needs to be further investigated in clinical populations. Trial Registration: PROSPERO CRD42021231027; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=231027 ",
doi="10.2196/35178",
url="https://www.jmir.org/2022/4/e35178",
url="http://www.ncbi.nlm.nih.gov/pubmed/35436239"
}


@Article{info:doi/10.2196/21055,
author="D{\textasciiacute}Ancona, Giuseppe
and Murero, Monica
and Feickert, Sebastian
and Kaplan, Hilmi
and {\"O}ner, Alper
and Ortak, Jasmin
and Ince, Hueseyin",
title="Implantation of an Innovative Intracardiac Microcomputer System for Web-Based Real-Time Monitoring of Heart Failure: Usability and Patients' Attitudes",
journal="JMIR Cardio",
year="2021",
month="Apr",
day="21",
volume="5",
number="1",
pages="e21055",
keywords="heart",
keywords="failure",
keywords="left atrial",
keywords="pressure",
keywords="intracardiac",
keywords="device",
keywords="monitoring",
keywords="implantable",
keywords="wireless",
keywords="transmission",
keywords="web-based",
abstract="Background: Heart failure (HF) management guided by the measurement of intracardiac and pulmonary pressure values obtained through innovative permanent intracardiac microsensors has been recently proposed as a valid strategy to individualize treatment and anticipate hemodynamic destabilization. These sensors have potential to reduce patient hospitalization rates and optimize quality of life. Objective: The aim of this study was to evaluate the usability and patients' attitudes toward a new permanent intracardiac device implanted to remotely monitor left intra-atrial pressures (V-LAP, Vectorious Medical Technologies, Tel Aviv, Israel) in patients with chronic HF. Methods: The V-LAP system is a miniaturized sensor implanted percutaneously across the interatrial septum. The system communicates wirelessly with a ``companion device'' (a wearable belt) that is placed on the patient's chest at the time of acquisition/transmission of left heart pressure measurements. At first follow-up after implantation, the patients and health care providers were asked to fill out a questionnaire on the usability of the system, ease in performing the various required tasks (data acquisition and transmission), and overall satisfaction. Replies to the questions were mainly given using a 5-point Likert scale (1: very poor, 2: poor, 3: average, 4: good, 5: excellent). Further patient follow-ups were performed at 3, 6, and 12 months. Results: Use and acceptance of the first 14 patients receiving the V-LAP technology worldwide and related health care providers have been analyzed to date. No periprocedural morbidity/mortality was observed. Before discharge, a tailored educational session was performed after device implantation with the patients and their health care providers. At the first follow-up, the mean score for overall comfort in technology use was 3.7 (SD 1.2) with 93\% (13/14) of patients succeeding in applying and operating the system independently. For health care providers, the mean score for overall ease and comfort in use of the technology was 4.2  (SD 0.8). No significant differences were found between the patients' and health care providers' replies to the questionnaires. There was a general trend for higher scores in patients' usability reports at later follow-ups, in which the score related to overall comfort with using the technology increased from 3.0 (SD 1.4) to 4.0 (SD 0.7) (P=.40) and comfort with wearing and adjusting the measuring thoracic belt increased from 2.8 (SD 1.0) to 4.2 (SD 0.4) (P=.02). Conclusions: Despite the gravity of their HF pathology and the complexity of their comorbid profile, patients are comfortable in using the V-LAP technology and, in the majority of cases, they can correctly and consistently acquire and transmit hemodynamic data. Although the overall patient/care provider satisfaction with the V-LAP system seems to be acceptable, improvements can be achieved after ameliorating the design of the measuring tools. Trial Registration: ClincalTrials.gov NCT03775161; https://clinicaltrials.gov/ct2/show/NCT03775161 ",
doi="10.2196/21055",
url="https://cardio.jmir.org/2021/1/e21055",
url="http://www.ncbi.nlm.nih.gov/pubmed/33881400"
}


@Article{info:doi/10.2196/17781,
author="Manzo, Maurizio
and Cavazos, Omar
and Huang, Zhenhua
and Cai, Liping",
title="Plasmonic and Hybrid Whispering Gallery Mode--Based Biosensors: Literature Review",
journal="JMIR Biomed Eng",
year="2021",
month="Apr",
day="12",
volume="6",
number="2",
pages="e17781",
keywords="plasmonic",
keywords="whispering gallery mode, microlasers, biomedical",
keywords="sensors",
abstract="Background: The term ``plasmonic'' describes the relationship between electromagnetic fields and metallic nanostructures. Plasmon-based sensors have been used innovatively to accomplish different biomedical tasks, including detection of cancer. Plasmonic sensors also have been used in biochip applications and biosensors and have the potential to be implemented as implantable point-of-care devices. Many devices and methods discussed in the literature are based on surface plasmon resonance (SPR) and localized SPR (LSPR). However, the mathematical background can be overwhelming for researchers at times. Objective: This review article discusses the theory of SPR, simplifying the underlying physics and bypassing many equations of SPR and LSPR. Moreover, we introduce and discuss the hybrid whispering gallery mode (WGM) sensing theory and its applications. Methods: A literature search in ScienceDirect was performed using keywords such as ``surface plasmon resonance,'' ``localized plasmon resonance,'' and ``whispering gallery mode/plasmonic.'' The search results retrieved many articles, among which we selected only those that presented a simple explanation of the SPR phenomena with prominent biomedical examples. Results: SPR, LSPR, tilted fiber Bragg grating, and hybrid WGM phenomena were explained and examples on biosensing applications were provided. Conclusions: This minireview presents an overview of biosensor applications in the field of biomedicine and is intended for researchers interested in starting to work in this field. The review presents the fundamental notions of plasmonic sensors and hybrid WGM sensors, thereby allowing one to get familiar with the terminology and underlying complex formulations of linear and nonlinear optics. ",
doi="10.2196/17781",
url="https://biomedeng.jmir.org/2021/2/e17781"
}


@Article{info:doi/10.2196/16973,
author="Nelson, C. Elizabeth
and Sools, M. Anneke
and Vollenbroek-Hutten, R. Miriam M.
and Verhagen, Tibert
and Noordzij, L. Matthijs",
title="Embodiment of Wearable Technology: Qualitative Longitudinal Study",
journal="JMIR Mhealth Uhealth",
year="2020",
month="Nov",
day="3",
volume="8",
number="11",
pages="e16973",
keywords="wearability",
keywords="implantable wearable",
keywords="body extension",
keywords="smart prosthesis",
keywords="implantable devices",
keywords="technology dependence",
keywords="cognitive prosthesis",
keywords="phenomenology",
keywords="embodied self-discrepancy",
keywords="technology addiction",
keywords="longitudinal qualitative design",
abstract="Background: Current technology innovations, such as wearables, have caused surprising reactions and feelings of deep connection to devices. Some researchers are calling mobile and wearable technologies cognitive prostheses, which are intrinsically connected to individuals as if they are part of the body, similar to a physical prosthesis. Additionally, while several studies have been performed on the phenomenology of receiving and wearing a physical prosthesis, it is unknown whether similar subjective experiences arise with technology. Objective: In one of the first qualitative studies to track wearables in a longitudinal investigation, we explore whether a wearable can be embodied similar to a physical prosthesis. We hoped to gain insights and compare the phases of embodiment (ie, initial adjustment to the prosthesis) and the psychological responses (ie, accept the prosthesis as part of their body) between wearables and limb prostheses. This approach allowed us to find out whether this pattern was part of a cyclical (ie, period of different usage intensity) or asymptotic (ie, abandonment of the technology) pattern. Methods: We adapted a limb prosthesis methodological framework to be applied to wearables and conducted semistructured interviews over a span of several months to assess if, how, and to what extent individuals come to embody wearables similar to prosthetic devices. Twelve individuals wore fitness trackers for 9 months, during which time interviews were conducted in the following three phases: after 3 months, after 6 months, and at the end of the study after 9 months. A deductive thematic analysis based on Murray's work was combined with an inductive approach in which new themes were discovered. Results: Overall, the individuals experienced technology embodiment similar to limb embodiment in terms of adjustment, wearability, awareness, and body extension. Furthermore, we discovered two additional themes of engagement/reengagement and comparison to another device or person. Interestingly, many participants experienced a rarely reported phenomenon in longitudinal studies where the feedback from the device was counterintuitive to their own beliefs. This created a blurring of self-perception and a dilemma of ``whom'' to believe, the machine or one's self. Conclusions: There are many similarities between the embodiment of a limb prosthesis and a wearable. The large overlap between limb and wearable embodiment would suggest that insights from physical prostheses can be applied to wearables and vice versa. This is especially interesting as we are seeing the traditionally ``dumb'' body prosthesis becoming smarter and thus a natural merging of technology and body. Future longitudinal studies could focus on the dilemma people might experience of whether to believe the information of the device over their own thoughts and feelings. These studies might take into account constructs, such as technology reliance, autonomy, and levels of self-awareness. ",
doi="10.2196/16973",
url="https://mhealth.jmir.org/2020/11/e16973",
url="http://www.ncbi.nlm.nih.gov/pubmed/33141093"
}