@Article{info:doi/10.2196/66886,
author="Shimotori, Daiki
and Kato, Kenji
and Yoshimi, Tatsuya
and Kondo, Izumi",
title="Validation of Gait Kinematics With Ramp and Stair Ascent and Descent Revealed by Markerless Motion Capture in Simulated Living Space: Test-Retest Reliability Study",
journal="JMIR Rehabil Assist Technol",
year="2025",
month="May",
day="15",
volume="12",
pages="e66886",
keywords="markerless motion capture",
keywords="living laboratory",
keywords="level walking",
keywords="ramp walking",
keywords="stair climbing",
keywords="kinematics",
keywords="measurement error",
keywords="absolute reliability",
keywords="gait",
keywords="walk",
keywords="stair",
keywords="ramp",
keywords="rehabilitation",
keywords="reliability",
keywords="simulated living space",
keywords="simulation",
keywords="motion capture",
keywords="gait kinematics",
abstract="Background: In recent years, there has been an increasing demand for markerless motion capture systems, which are being widely used in biomechanical and clinical research. Furthermore, by using a markerless motion capture system in a laboratory environment that mimics living spaces, the data acquired on various activities of daily living, such as level walking, ramp walking, and stair ascent and descent, should more closely resemble that of real-life activities. However, the absolute reliability of gait parameters in this context is still unclear. Objective: The aim of this study was to evaluate the reliability of a markerless motion capture system in assessing the ascent and descent of ramps and stairs during walking in a simulated living space. Methods: A total of 21 healthy participants performed level walking, ramp and stair ascent and descent on two separate days, with at least a 24-hour interval between sessions. Joint angles were measured using 27 synchronized cameras with a markerless motion capture application, Theia3D (Theia Markerless Inc), and analyzed in Visual3d for all planes of motion at the hip-, knee-, and ankle-joints. The absolute reliability of day-to-day reproducibility was assessed using full-curve analysis (root mean square difference [RMSD]) and discrete point analysis of gait events using the standard error of measurement (SEM). SEM was calculated only for level walking and ramp ascent and descent, where gait events were correctly detected. Results: The SEM values for level walking and ramp ascent and descent were all below the 5-degree threshold. However, while RMSD values were generally below 5{\textdegree}, this threshold was exceeded for knee-joint flexion-extension angles during ramp ascent and stair ascent (5.07{\textdegree} and 5.64{\textdegree}, respectively). Conclusions: The markerless motion capture system in the living laboratory setting demonstrated a high degree of accuracy for various environments and gait types. The low SEM values obtained indicate good reliability for joint angle measurements across different days. The slightly higher RMSD values for knee-joint angles during ramp and stair ascent may reflect the system's ability to capture the adaptations in joint kinematics in response to changes in gait conditions. These measurements in a living laboratory environment validated the absolute reliability of various gait parameters not only in level walking but also in ramp and stair ascent and descent. The findings suggest potential clinical applications and research opportunities, including the development of assistive devices and robots, using markerless motion capture in more natural living situations, rather than in controlled environments. Trial Registration: UMIN Clinical Trials Registry UMIN000049284; https://center6.umin.ac.jp/cgi-open-bin/ctr\_e/ctr\_view.cgi?recptno=R000056126 ",
doi="10.2196/66886",
url="https://rehab.jmir.org/2025/1/e66886"
}


@Article{info:doi/10.2196/54921,
author="Zola Matuvanga, Tr{\'e}sor
and Paviotti, Antea
and Bikioli Bolombo, Freddy
and Lemey, Gwen
and Larivi{\`e}re, Ynke
and Salloum, Maha
and Isekah Osang'ir, Bernard
and Esanga Longomo, Emmanuel
and Milolo, Solange
and Matangila, Junior
and Maketa, Vivi
and Mitashi, Patrick
and Van Damme, Pierre
and Muhindo-Mavoko, Hypolite
and Van geertruyden, Jean-Pierre",
title="Long-Term Experiences of Health Care Providers Using Iris Scanning as an Identification Tool in a Vaccine Trial in the Democratic Republic of the Congo: Qualitative Study",
journal="JMIR Form Res",
year="2025",
month="Mar",
day="6",
volume="9",
pages="e54921",
keywords="iris scan",
keywords="vaccine trial",
keywords="iris",
keywords="perception",
keywords="experience",
keywords="views",
keywords="biometric identification",
keywords="Democratic Republic of the Congo",
abstract="Background: Iris scanning has increasingly been used for biometric identification over the past decade, with continuous advancements and expanding applications. To better understand the acceptability of this technology, we report the long-term experiences of health care providers and frontline worker participants with iris scanning as an identification tool in the EBL2007 Ebola vaccine trial conducted in the Democratic Republic of the Congo. Objective: This study aims to document the long-term experiences of using iris scanning for identity verification throughout the vaccine trial. Methods: Two years after the start of the EBL2007 vaccine trial (February to March 2022), 69 trial participants---including nurses, first aid workers, midwives, and community health workers---were interviewed through focus group discussions. Additionally, 13 in-depth individual interviews were conducted with physicians involved in the trial, iris scan operators, trial staff physicians, and trial participants who declined iris scanning. Qualitative content analysis was used to identify key themes. Results: Initially, interviewees widely accepted the iris scan and viewed it as a distinctive tool for identifying participants in the EBL2007 vaccine trial. However, over time, perceptions became less favorable. Some participants expressed concerns that their vision had diminished shortly after using the tool and continued to decline until the end of the study. Others reported experiencing perceived vision loss long after the trial had concluded. However, no vision impairment was reported as an adverse event or assessed in the trial as being linked to the iris scan, which uses a previously certified safe infrared light for scanning. Conclusions: Our findings highlight the sustained acceptability and perceived high accuracy of the iris scan tool for uniquely identifying adult participants in a vaccine trial over time. Continued efforts to systematically disseminate and reinforce information about the function and safety of this technology are essential. Clearly presenting iris scanning as a safe procedure could help dispel misconceptions, concerns, and perceived risks among potential users in vaccine trials. ",
doi="10.2196/54921",
url="https://formative.jmir.org/2025/1/e54921",
url="http://www.ncbi.nlm.nih.gov/pubmed/40053756"
}


@Article{info:doi/10.2196/60685,
author="Jansen, Marjolein
and van Iperen, D. Ingrid
and Kroner, Anke
and Hemler, Raphael
and Dekker-Holverda, Esther
and Spronk, E. Peter",
title="Kangaroo Stimulation Game in Tracheostomized Intensive Care--Related Dysphagia: Interventional Feasibility Study",
journal="JMIR Serious Games",
year="2025",
month="Mar",
day="5",
volume="13",
pages="e60685",
keywords="dysphagia",
keywords="swallowing",
keywords="intensive care",
keywords="ICU",
keywords="swallowing disturbance",
keywords="kangaroo stimulation",
keywords="game",
keywords="feasibility study",
keywords="surface electromyography",
keywords="training",
keywords="exercise",
keywords="Rephagia biofeedback",
keywords="muscle strength",
keywords="stamina",
keywords="timing",
keywords="tracheostomy",
keywords="clinical",
keywords="feasibility",
abstract="Background: Dysphagia is common in intensive care unit (ICU) patients. Using surface electromyography (sEMG) signals as biofeedback training exercises might offer a promising path to improving swallowing function. The Rephagia biofeedback system uses sEMG to assess muscle strength, stamina, and timing of the swallowing action. Objectives: The aim of this study was to evaluate the feasibility of the Rephagia system in ICU patients with dysphagia. Methods: This feasibility study included patients admitted to a 14-bed mixed medical-surgical ICU. All patients underwent a new tracheostomy placement during ICU stay due to persistent aspiration and ICU-acquired weakness, accompanied by verified dysphagia. Following Rephagia training, patients completed a questionnaire assessing comprehension, satisfaction, and motivation. Swallowing characteristics were assessed via mean sEMG peak values during exercise. Results: Twenty patients with a mean age of 69.4 (SD 8.2) years were included. The means of sEMG values at the beginning of a measurement were not significantly different at baseline versus everyone's last measurement (52 {\textmu}V [23 {\textmu}V] vs 57 {\textmu}V [22 {\textmu}V]; P=.50). The means of sEMG values obtained at the end of a measurement were not significantly different at baseline versus everyone's last measurement (56 {\textmu}V [18 {\textmu}V] vs 59 {\textmu}V [23 {\textmu}V]; P=.62). However, dysphagia improved in all patients. Patients understood the importance of the game in relation to their swallowing problems (16/80, 89\%), which kept them motivated to participate in the training sessions (9/18, 50\%). Conclusions: The Rephagia biofeedback system for stimulating swallowing actions in tracheotomized ICU patients with dysphagia is feasible. No relation was found between clinical improvement in swallowing function and sEMG signals. ",
doi="10.2196/60685",
url="https://games.jmir.org/2025/1/e60685"
}


@Article{info:doi/10.2196/63004,
author="De Silva, Upeka
and Madanian, Samaneh
and Olsen, Sharon
and Templeton, Michael John
and Poellabauer, Christian
and Schneider, L. Sandra
and Narayanan, Ajit
and Rubaiat, Rahmina",
title="Clinical Decision Support Using Speech Signal Analysis: Systematic Scoping Review of Neurological Disorders",
journal="J Med Internet Res",
year="2025",
month="Jan",
day="13",
volume="27",
pages="e63004",
keywords="digital health",
keywords="health informatics",
keywords="digital biomarker",
keywords="speech analytics",
keywords="artificial intelligence",
keywords="machine learning",
abstract="Background: Digital biomarkers are increasingly used in clinical decision support for various health conditions. Speech features as digital biomarkers can offer insights into underlying physiological processes due to the complexity of speech production. This process involves respiration, phonation, articulation, and resonance, all of which rely on specific motor systems for the preparation and execution of speech. Deficits in any of these systems can cause changes in speech signal patterns. Increasing efforts are being made to develop speech-based clinical decision support systems. Objective: This systematic scoping review investigated the technological revolution and recent digital clinical speech signal analysis trends to understand the key concepts and research processes from clinical and technical perspectives. Methods: A systematic scoping review was undertaken in 6 databases guided by a set of research questions. Articles that focused on speech signal analysis for clinical decision-making were identified, and the included studies were analyzed quantitatively. A narrower scope of studies investigating neurological diseases were analyzed using qualitative content analysis. Results: A total of 389 articles met the initial eligibility criteria, of which 72 (18.5\%) that focused on neurological diseases were included in the qualitative analysis. In the included studies, Parkinson disease, Alzheimer disease, and cognitive disorders were the most frequently investigated conditions. The literature explored the potential of speech feature analysis in diagnosis, differentiating between, assessing the severity and monitoring the treatment of neurological conditions. The common speech tasks used were sustained phonations, diadochokinetic tasks, reading tasks, activity-based tasks, picture descriptions, and prompted speech tasks. From these tasks, conventional speech features (such as fundamental frequency, jitter, and shimmer), advanced digital signal processing--based speech features (such as wavelet transformation--based features), and spectrograms in the form of audio images were analyzed. Traditional machine learning and deep learning approaches were used to build predictive models, whereas statistical analysis assessed variable relationships and reliability of speech features. Model evaluations primarily focused on analytical validations. A significant research gap was identified: the need for a structured research process to guide studies toward potential technological intervention in clinical settings. To address this, a research framework was proposed that adapts a design science research methodology to guide research studies systematically. Conclusions: The findings highlight how data science techniques can enhance speech signal analysis to support clinical decision-making. By combining knowledge from clinical practice, speech science, and data science within a structured research framework, future research may achieve greater clinical relevance. ",
doi="10.2196/63004",
url="https://www.jmir.org/2025/1/e63004",
url="http://www.ncbi.nlm.nih.gov/pubmed/39804693"
}


@Article{info:doi/10.2196/62770,
author="Wu, Sixuan
and Song, Kefan
and Cobb, Jason
and Adams, T. Alexander",
title="Pump-Free Microfluidics for Cell Concentration Analysis on Smartphones in Clinical Settings (SmartFlow): Design, Development, and Evaluation",
journal="JMIR Biomed Eng",
year="2024",
month="Dec",
day="23",
volume="9",
pages="e62770",
keywords="mobile health",
keywords="mHealth",
keywords="ubiquitous health",
keywords="smartphone",
keywords="chip",
keywords="microscope",
keywords="microfluidics",
keywords="cells counting, body fluid analysis, blood test, urinalysis, computer vision, machine learning",
keywords="fluid",
keywords="cell",
keywords="cellular",
keywords="concentration",
abstract="Background: Cell concentration in body fluid is an important factor for clinical diagnosis. The traditional method involves clinicians manually counting cells under microscopes, which is labor-intensive. Automated cell concentration estimation can be achieved using flow cytometers; however, their high cost limits accessibility. Microfluidic systems, although cheaper than flow cytometers, still require high-speed cameras and syringe pumps to drive the flow and ensure video quality. In this paper, we present SmartFlow, a low-cost solution for cell concentration estimation using smartphone-based computer vision on 3D-printed, pump-free microfluidic platforms. Objective: The objective was to design and fabricate microfluidic chips, coupled with clinical utilities, for cell counting and concentration analysis. We answered the following research questions (RQs): RQ1, Can gravity drive the flow within the microfluidic chips, eliminating the need for external pumps? RQ2, How does the microfluidic chip design impact video quality for cell analysis? RQ3, Can smartphone-captured videos be used to estimate cell count and concentration in microfluidic chips? Methods: To answer the 3 RQs, 2 experiments were conducted. In the cell flow velocity experiment, diluted sheep blood flowed through the microfluidic chips with and without a bottleneck design to answer RQ1 and RQ2, respectively. In the cell concentration analysis experiment, sheep blood diluted into 13 concentrations flowed through the microfluidic chips while videos were recorded by smartphones for the concentration measurement. Results: In the cell flow velocity experiment, we designed and fabricated 2 versions of microfluidic chips. The ANOVA test (Straight: F6, 99=6144.45, P<.001; Bottleneck: F6, 99=3475.78, P<.001) showed the height difference had a significant impact on the cell velocity, which implied gravity could drive the flow. The video sharpness analysis demonstrated that video quality followed an exponential decay with increasing height differences (video quality=100e--k{\texttimes}Height) and a bottleneck design could effectively preserve video quality (Straight: R2=0.95, k=4.33; Bottleneck: R2=0.91, k=0.59). Samples from the 13 cell concentrations were used for cell counting and cell concentration estimation analysis. The accuracy of cell counting (n=35, 60-second samples, R2=0.96, mean absolute error=1.10, mean squared error=2.24, root mean squared error=1.50) and cell concentration regression (n=39, 150-second samples, R2=0.99, mean absolute error=0.24, mean squared error=0.11, root mean squared error=0.33 on a logarithmic scale, mean average percentage error=0.25) were evaluated using 5-fold cross-validation by comparing the algorithmic estimation to ground truth. Conclusions: In conclusion, we demonstrated the importance of the flow velocity in a microfluidic system, and we proposed SmartFlow, a low-cost system for computer vision--based cellular analysis. The proposed system could count the cells and estimate cell concentrations in the samples. ",
doi="10.2196/62770",
url="https://biomedeng.jmir.org/2024/1/e62770"
}


@Article{info:doi/10.2196/57373,
author="Loro, La{\'i}s Fernanda
and Martins, Riane
and Ferreira, Barcellos Jana{\'i}na
and de Araujo, Pereira Cintia Laura
and Prade, Rene Lucio
and Both, Bonato Cristiano
and Nobre, Nobre J{\'e}ferson Campos
and Monteiro, Borba Mariane
and Dal Lago, Pedro",
title="Validation of a Wearable Sensor Prototype for Measuring Heart Rate to Prescribe Physical Activity: Cross-Sectional Exploratory Study",
journal="JMIR Biomed Eng",
year="2024",
month="Dec",
day="11",
volume="9",
pages="e57373",
keywords="heart rate",
keywords="wearable device",
keywords="HR",
keywords="biosensor",
keywords="physiological monitor",
keywords="wearable system",
keywords="medical device",
keywords="mobile phone",
abstract="Background: Wearable sensors are rapidly evolving, particularly in health care, due to their ability to facilitate continuous or on-demand physiological monitoring. Objective: This study aimed to design and validate a wearable sensor prototype incorporating photoplethysmography (PPG) and long-range wide area network technology for heart rate (HR) measurement during a functional test. Methods: We conducted a transversal exploratory study involving 20 healthy participants aged between 20 and 30 years without contraindications for physical exercise. Initially, our laboratory developed a pulse wearable sensor prototype for HR monitoring. Following this, the participants were instructed to perform the Incremental Shuttle Walk Test while wearing the Polar H10 HR chest strap sensor (the reference for HR measurement) and the wearable sensor. This test allowed for real-time comparison of HR responses between the 2 devices. Agreement between these measurements was determined using the intraclass correlation coefficient (ICC3.1) and Lin concordance correlation coefficient. The mean absolute percentage error was calculated to evaluate reliability or validity. Cohen d was used to calculate the agreement's effect size. Results: The mean differences between the Polar H10 and the wearable sensor during the test were --2.6 (95\% CI --3.5 to --1.8) for rest HR, --4.1 (95\% CI --5.3 to --3) for maximum HR, --2.4 (95\% CI --3.5 to --1.4) for mean test HR, and --2.5 (95\% CI --3.6 to --1.5) for mean recovery HR. The mean absolute percentage errors were --3\% for rest HR, --2.2\% for maximum HR, --1.8\% for mean test HR, and --1.6\% for recovery HR. Excellent agreement was observed between the Polar H10 and the wearable sensor for rest HR (ICC3.1=0.96), mean test HR (ICC3.1=0.92), and mean recovery HR (ICC3.1=0.96). The agreement for maximum HR (ICC3.1=0.78) was considered good. By the Lin concordance correlation coefficient, the agreement was found to be substantial for rest HR (rc=0.96) and recovery HR (rc=0.96), moderate for mean test HR (rc=0.92), and poor for maximum HR (rc=0.78). The power of agreement between the Polar H10 and the wearable sensor prototype was large for baseline HR (Cohen d=0.97), maximum HR (Cohen d=1.18), and mean recovery HR (Cohen d=0.8) and medium for mean test HR (Cohen d= 0.76). Conclusions: The pulse-wearable sensor prototype tested in this study proves to be a valid tool for monitoring HR at rest, during functional tests, and during recovery compared with the Polar H10 reference device used in the laboratory setting. ",
doi="10.2196/57373",
url="https://biomedeng.jmir.org/2024/1/e57373",
url="http://www.ncbi.nlm.nih.gov/pubmed/39661434"
}


@Article{info:doi/10.2196/58892,
author="Chan, Zhong Pin
and Jin, Eric
and Jansson, Miia
and Chew, Jocelyn Han Shi",
title="AI-Based Noninvasive Blood Glucose Monitoring: Scoping Review",
journal="J Med Internet Res",
year="2024",
month="Nov",
day="19",
volume="26",
pages="e58892",
keywords="artificial intelligence",
keywords="blood glucose",
keywords="diabetes",
keywords="noninvasive",
keywords="self-monitoring",
keywords="machine learning",
keywords="scoping review",
keywords="monitoring",
keywords="management",
keywords="health informatics",
keywords="deep learning",
keywords="accuracy",
keywords="heterogeneity",
keywords="mobile phone",
abstract="Background: Current blood glucose monitoring (BGM) methods are often invasive and require repetitive pricking of a finger to obtain blood samples, predisposing individuals to pain, discomfort, and infection. Noninvasive blood glucose monitoring (NIBGM) is ideal for minimizing discomfort, reducing the risk of infection, and increasing convenience. Objective: This review aimed to map the use cases of artificial intelligence (AI) in NIBGM. Methods: A systematic scoping review was conducted according to the Arksey O'Malley five-step framework. Eight electronic databases (CINAHL, Embase, PubMed, Web of Science, Scopus, The Cochrane-Central Library, ACM Digital Library, and IEEE Xplore) were searched from inception until February 8, 2023. Study selection was conducted by 2 independent reviewers, descriptive analysis was conducted, and findings were presented narratively. Study characteristics (author, country, type of publication, study design, population characteristics, mean age, types of noninvasive techniques used, and application, as well as characteristics of the BGM systems) were extracted independently and cross-checked by 2 investigators. Methodological quality appraisal was conducted using the Checklist for assessment of medical AI. Results: A total of 33 papers were included, representing studies from Asia, the United States, Europe, the Middle East, and Africa published between 2005 and 2023. Most studies used optical techniques (n=19, 58\%) to estimate blood glucose levels (n=27, 82\%). Others used electrochemical sensors (n=4), imaging (n=2), mixed techniques (n=2), and tissue impedance (n=1). Accuracy ranged from 35.56\% to 94.23\% and Clarke error grid (A+B) ranged from 86.91\% to 100\%. The most popular machine learning algorithm used was random forest (n=10) and the most popular deep learning model was the artificial neural network (n=6). The mean overall checklist for assessment of medical AI score on the included papers was 33.5 (SD 3.09), suggesting an average of medium quality. The studies reviewed demonstrate that some AI techniques can accurately predict glucose levels from noninvasive sources while enhancing comfort and ease of use for patients. However, the overall range of accuracy was wide due to the heterogeneity of models and input data. Conclusions: Efforts are needed to standardize and regulate the use of AI technologies in BGM, as well as develop consensus guidelines and protocols to ensure the quality and safety of AI-assisted monitoring systems. The use of AI for NIBGM is a promising area of research that has the potential to revolutionize diabetes management. ",
doi="10.2196/58892",
url="https://www.jmir.org/2024/1/e58892"
}


@Article{info:doi/10.2196/58466,
author="Lin, Yu-Chun
and Yan, Huang-Ting
and Lin, Chih-Hsueh
and Chang, Hen-Hong",
title="Identifying and Estimating Frailty Phenotypes by Vocal Biomarkers: Cross-Sectional Study",
journal="J Med Internet Res",
year="2024",
month="Nov",
day="8",
volume="26",
pages="e58466",
keywords="frailty phenotypes",
keywords="older adults",
keywords="successful aging",
keywords="vocal biomarkers",
keywords="frailty",
keywords="phenotype",
keywords="vocal biomarker",
keywords="cross-sectional",
keywords="gerontology",
keywords="geriatrics",
keywords="older adult",
keywords="Taiwan",
keywords="energy-based",
keywords="hybrid-based",
keywords="sarcopenia",
abstract="Background: Researchers have developed a variety of indices to assess frailty. Recent research indicates that the human voice reflects frailty status. Frailty phenotypes are seldom discussed in the literature on the aging voice. Objective: This study aims to examine potential phenotypes of frail older adults and determine their correlation with vocal biomarkers. Methods: Participants aged ?60 years who visited the geriatric outpatient clinic of a teaching hospital in central Taiwan between 2020 and 2021 were recruited. We identified 4 frailty phenotypes: energy-based frailty, sarcopenia-based frailty, hybrid-based frailty--energy, and hybrid-based frailty--sarcopenia. Participants were asked to pronounce a sustained vowel ``/a/'' for approximately 1 second. The speech signals were digitized and analyzed. Four voice parameters---the average number of zero crossings (A1), variations in local peaks and valleys (A2), variations in first and second formant frequencies (A3), and spectral energy ratio (A4)---were used for analyzing changes in voice. Logistic regression was used to elucidate the prediction model. Results: Among 277 older adults, an increase in A1 values was associated with a lower likelihood of energy-based frailty (odds ratio [OR] 0.81, 95\% CI 0.68-0.96), whereas an increase in A2 values resulted in a higher likelihood of sarcopenia-based frailty (OR 1.34, 95\% CI 1.18-1.52). Respondents with larger A3 and A4 values had a higher likelihood of hybrid-based frailty--sarcopenia (OR 1.03, 95\% CI 1.002-1.06) and hybrid-based frailty--energy (OR 1.43, 95\% CI 1.02-2.01), respectively. Conclusions: Vocal biomarkers might be potentially useful in estimating frailty phenotypes. Clinicians can use 2 crucial acoustic parameters, namely A1 and A2, to diagnose a frailty phenotype that is associated with insufficient energy or reduced muscle function. The assessment of A3 and A4 involves a complex frailty phenotype. ",
doi="10.2196/58466",
url="https://www.jmir.org/2024/1/e58466"
}


@Article{info:doi/10.2196/60858,
author="Chandrashekar, BS
and Lobo, Clement Oliver
and Fusco, Irene
and Madeddu, Francesca
and Zingoni, Tiziano",
title="Effectiveness of 675-nm Wavelength Laser Therapy in the Treatment of Androgenetic Alopecia Among Indian Patients:  Clinical Experimental Study",
journal="JMIR Dermatol",
year="2024",
month="Sep",
day="23",
volume="7",
pages="e60858",
keywords="androgenetic alopecia",
keywords="AGA",
keywords="675-nm laser",
keywords="Indian patients",
keywords="hair restoration",
keywords="effectiveness",
keywords="laser therapy",
keywords="therapy",
keywords="treatment",
keywords="Indian",
keywords="patients",
keywords="patient",
keywords="India",
keywords="hair loss",
keywords="hair",
keywords="laser stimulation",
keywords="hair density",
abstract="Background: Androgenetic alopecia (AGA) is the most prevalent cause of hair loss around the world. Objective: The purpose of this study was to evaluate the efficacy of laser stimulation with a 675-nm wavelength for the treatment of AGA in male and female Indian patients. Methods: A total of 20 Indian healthy patients aged 23-57 years who presented a grade of alopecia stage I to stage V underwent one single pass with a 675-nm laser to the scalp area twice a week for a total of 8 sessions, followed by once a week for 4 sessions and once in 2 weeks for 2 sessions. There are 14 laser treatments in total. Macro- and dermatoscopic images have been acquired at T0 (baseline) and T1 (4 months). The vertex, frontal, and parietal areas of the scalp were evaluated. Many parameters were analyzed including hair count and hair density of terminal; mean thickness; vellus follicles; total follicular units; units with 1 hair, 2 hairs, 3 hairs, 4 hairs, and >4 hairs; unit density; and average hair/unit. Results: The macroimages and dermatoscopic evaluations showed good improvement over the entire treated area, with a clear increase in the number of hairs and hair thickness. General parameters such as hair count and hair density showed a percentage increase of around 17\%. The hair mean thickness parameters showed a significant (P<.001) percentage increase of 13.91\%. Similar results were obtained for terminal and vellus hair: terminal hair count and hair density significantly (P=.04 and P=.01, respectively) increased by 17.45\%, vellus hair count increased by 16.67\% (P=.06), and the density of vellus hair increased by 16.61\% (P=.06). Conclusions: The study findings demonstrate that the 675-nm laser system improved AGA in Indian patients, facilitating the anagen phase and improving hair density and other positive hair parameters. ",
doi="10.2196/60858",
url="https://derma.jmir.org/2024/1/e60858"
}


@Article{info:doi/10.2196/52167,
author="Chikwetu, Lucy
and Vakili, Parker
and Takais, Andrew
and Younes, Rabih",
title="Central Hemodynamic and Thermoregulatory Responses to Food Intake as Potential Biomarkers for Eating Detection: Systematic Review",
journal="Interact J Med Res",
year="2024",
month="Sep",
day="10",
volume="13",
pages="e52167",
keywords="eating detection",
keywords="eating moment recognition",
keywords="postprandial physiological responses",
keywords="postprandial physiology",
keywords="eating",
keywords="food",
keywords="consumption",
keywords="postprandial",
keywords="hemodynamics prandial",
keywords="thermoregulation",
keywords="physiological",
keywords="heart rate",
keywords="vital",
keywords="vitals",
keywords="wearable",
keywords="wearables",
keywords="thermoregulatory hemodynamic",
keywords="biomarker",
keywords="biomarkers",
keywords="diet",
keywords="dietary",
keywords="monitoring",
keywords="detect",
keywords="detection",
keywords="detecting",
keywords="synthesis",
keywords="review methods",
keywords="review methodology",
keywords="systematic",
keywords="sensor",
keywords="sensors",
keywords="digital health",
abstract="Background: Diet-related diseases, such as type 2 diabetes, require strict dietary management to slow down disease progression and call for innovative management strategies. Conventional diet monitoring places a significant memory burden on patients, who may not accurately remember details of their meals and thus frequently falls short in preventing disease progression. Recent advances in sensor and computational technologies have sparked interest in developing eating detection platforms. Objective: This review investigates central hemodynamic and thermoregulatory responses as potential biomarkers for eating detection. Methods: We searched peer-reviewed literature indexed in PubMed, Web of Science, and Scopus on June 20, 2022, with no date limits. We also conducted manual searches in the same databases until April 21, 2024. We included English-language papers demonstrating the impact of eating on central hemodynamics and thermoregulation in healthy individuals. To evaluate the overall study quality and assess the risk of bias, we designed a customized tool inspired by the Cochrane assessment framework. This tool has 4 categories: high, medium, low, and very low. A total of 2 independent reviewers conducted title and abstract screening, full-text review, and study quality and risk of bias analysis. In instances of disagreement between the 2 reviewers, a third reviewer served as an adjudicator. Results: Our search retrieved 11,450 studies, and 25 met our inclusion criteria. Among the 25 included studies, 32\% (8/25) were classified as high quality, 52\% (13/25) as medium quality, and 16\% (4/25) as low quality. Furthermore, we found no evidence of publication bias in any of the included studies. A consistent postprandial increase in heart rate, cardiac output, and stroke volume was observed in at least 95\% (heart rate: 19/19, cardiac output: 18/19, stroke volume: 11/11) of the studies that investigated these variables' responses to eating. Specifically, cardiac output increased by 9\%-100\%, stroke volume by 18\%-41\%, and heart rate by 6\%-21\% across these studies. These changes were statistically significant (P<.05). In contrast, the 8 studies that investigated postprandial thermoregulatory effects displayed grossly inconsistent results, showing wide variations in response with no clear patterns of change, indicating a high degree of variability among these studies. Conclusions: Our findings demonstrate that central hemodynamic responses, particularly heart rate, hold promise for wearable-based eating detection, as cardiac output and stroke volume cannot be measured by any currently available noninvasive medical or consumer-grade wearables. Trial Registration: PROSPERO CRD42022360600; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=360600 ",
doi="10.2196/52167",
url="https://www.i-jmr.org/2024/1/e52167"
}