@Article{info:doi/10.2196/53460,
author="Ramkumar, Vidya
and Joshi B, Deepashree
and Prabhakar, Anil
and Hall, W. James
and Vaidyanath, Ramya",
title="Development and Beta Validation of an mHealth-Based Hearing Screener (SRESHT) for Young Children in Resource-Limited Countries: Pilot Validation Study",
journal="JMIR Form Res",
year="2025",
month="Jan",
day="13",
volume="9",
pages="e53460",
keywords="audiometry",
keywords="mHealth",
keywords="devices",
keywords="wireless",
keywords="tablet-based screening",
keywords="childhood hearing loss",
keywords="early hearing detection and intervention",
keywords="tablets",
keywords="children",
keywords="neonates",
keywords="hearing loss",
keywords="infants",
keywords="development",
keywords="validation",
keywords="mobile phones",
abstract="Background: The prevalence of hearing loss in infants in India varies between 4 and 5 per 1000. Objective-based otoacoustic emissions and auditory brainstem response have been used in high-income countries for establishing early hearing screening and intervention programs. Nevertheless, the use of objective screening tests in low- and middle-income countries (LMICs) such as India is not feasible. Mobile health (mHealth) solutions have been demonstrated to be a viable option for hearing screening in LMICs. Objective: This study aims to develop and beta-validate an affordable hearing screener for children younger than 6 years of age to identify moderately severe or higher degrees of hearing loss. Methods: In phase 1, a mHealth-based hearing screener (SRESHT) was developed using a single board computer with wireless commercial headphones and speakers as transducers, which were calibrated according to the standard procedure. Three subjective hearing screening modules were conceptualized and developed for different age groups: (1) behavioral observation audiometry--screening for infants aged from 0 to 1 year; (2) speech spectrum awareness task--screening for children 1 to 3 years old; and (3) speech recognition task--screening for children 3 to 6 years old. Different auditory stimuli for the screening modules were generated and suitability was assessed: (1) noisemakers, animal sounds, and environmental sounds for infants (birth to 1 year old); (2) animal sounds and nonsense syllables for children (1 to 3 years old); and (3) eighteen picturable spondee words for children (3 to 6 years old). In phase 2, the SRESHT screener was beta-validated in children aged below 6 years to establish the agreement between SRESHT modules and the gold-standard procedure in identifying moderately severe and higher degrees of hearing loss. Results: Off-the-shelf commercial speakers and headphones were selected and calibrated. On comparison of stimuli for behavioral observation audiometry on 15 children, Noisemaker stimuli were found suitable based on the average minimum response levels. On comparison of different stimuli for speech spectrum awareness task on 15 children, animal sounds were found to be suitable. On familiarity check of 18 spondee words for speech recognition task among 20 children, 12 spondee words had the eligibility cutoff (85\%) and a presentation level of 5 dB SL (re-pure tone threshold) was sufficient to achieve 80\% psychometric function. In phase 2, a total of 55 children aged 0 to 6 years (31 normal hearing and 24 hearing impairment) underwent SRESHT screening for beta validation. Cohen $\kappa$ indicated that the overall SRESHT screener had a very good agreement ($\kappa$=0.82) with gold-standard audiometric screening for identifying moderately severe and higher degrees of hearing loss. Conclusions: The development and beta validation of the SRESHT screener using the selected auditory stimuli showed that the stimuli were suitable for screening children. ",
doi="10.2196/53460",
url="https://formative.jmir.org/2025/1/e53460"
}


@Article{info:doi/10.2196/57433,
author="Palucci Vieira, H. Luiz
and Clemente, Manuel Filipe
and Chang Marquez, Armando Felipe
and Rea Olivares, Manuel Walter
and Vargas Villafuerte, R. Kelly
and Carpes, P. Felipe",
title="Accuracy Standards of Wearable Technologies for Assessment of Soccer Kicking: Protocol for a Systematic Literature Review",
journal="JMIR Res Protoc",
year="2024",
month="Nov",
day="4",
volume="13",
pages="e57433",
keywords="skill-related performance",
keywords="shooting",
keywords="team sports",
keywords="sports engineering",
keywords="measurement error",
keywords="validity",
keywords="reliability",
keywords="quality control",
abstract="Background: Wearable technology is widely applied in performance monitoring, an integral part of sports and exercise sciences. The kick movement in soccer exemplifies a sports technique that could benefit from appropriate biomechanics assessment methodologies. However, the accuracy of wearables in quantifying soccer kick mechanics, particularly under field conditions, remains unclear. Objective: This study aims to present a protocol for a systematic review to discuss the measurement properties (validity, reliability, and/or accuracy aspects) of wearable technology systems explicitly used to measure ball-kicking features in soccer. Methods: This review protocol was preregistered in the Open Science Framework. A total of 2 authors will perform searches in major electronic databases using specific keyword combinations in PubMed, Physical Therapy and Sports Medicine, Web of Science, ProQuest, IEEE Xplore, EBSCOHost, and Scopus. Following a specific population, intervention, comparison, outcome framework (population: soccer players and/or collected human data in a football-related environment; intervention: at least 1 wearable used; comparator: criterion measures, repeated testing sessions and/or actual values; outcome: ball kicking data), studies will be screened based on predetermined inclusion and exclusion criteria. The methodological quality of the included studies will be assessed using the ``consensus-based standards for the selection of health measurement instruments'' checklist (in studies concerning validity or reliability) or the ``quality assessment of diagnostic accuracy studies'' tool (in studies concerning accuracy). Data extraction will be conducted to determine the level of evidence according to the ``best evidence synthesis method,'' and an evidence gap map will be constructed. The Cohen $\kappa$ coefficient will be used to estimate the interevaluator agreement. Results: This ongoing systematic review has completed database searches and is currently in the screening phase. Depending on the number and consistency of studies, results may be presented by meta-analysis or qualitative synthesis, with subgroup analyses considering factors such as gender, age, and playing level. The final results are expected by July 2024, with manuscript submission anticipated by November 2024. Conclusions: Our study will provide a comprehensive summary of the highest level of evidence available on the use of wearables for the assessment of soccer kick mechanics, providing practical guidance for athletes and sports sciences professionals regarding the validity and reliability aspects of using wearable technology to measure ball-kicking features in soccer. Trial Registration: OSF registries https://osf.io/zm3j6 International Registered Report Identifier (IRRID): DERR1-10.2196/57433 ",
doi="10.2196/57433",
url="https://www.researchprotocols.org/2024/1/e57433"
}


@Article{info:doi/10.2196/54159,
author="Wodu, Obinuchi Chioma
and Sweeney, Gillian
and Slachetka, Milena
and Kerr, Andrew",
title="Stroke Survivors' Interaction With Hand Rehabilitation Devices: Observational Study",
journal="JMIR Biomed Eng",
year="2024",
month="Jun",
day="26",
volume="9",
pages="e54159",
keywords="stroke",
keywords="rehabilitation",
keywords="hand rehabilitation devices",
keywords="accessibility",
keywords="stroke survivors",
keywords="rehabilitation technologies",
abstract="Background: The hand is crucial for carrying out activities of daily living as well as social interaction. Functional use of the upper limb is affected in up to 55\% to 75\% of stroke survivors 3 to 6 months after stroke. Rehabilitation can help restore function, and several rehabilitation devices have been designed to improve hand function. However, access to these devices is compromised in people with more severe loss of function. Objective: In this study, we aimed to observe stroke survivors with poor hand function interacting with a range of commonly used hand rehabilitation devices. Methods: Participants were engaged in an 8-week rehabilitation intervention at a technology-enriched rehabilitation gym. The participants spent 50-60 minutes of the 2-hour session in the upper limb section at least twice a week. Each participant communicated their rehabilitation goals, and an Action Research Arm Test (ARAT) was used to measure and categorize hand function as poor (scores of 0-9), moderate (scores of 10-56), or good (score of 57). Participants were observed during their interactions with 3 hand-based rehabilitation devices that focused on hand rehabilitation: the GripAble, NeuroBall, and Semi-Circular Peg Board. Observations of device interactions were recorded for each session. Results: A total of 29 participants were included in this study, of whom 10 (34\%) had poor hand function, 17 (59\%) had moderate hand function, and 2 (7\%) had good hand function. There were no differences in the age and years after stroke among participants with poor hand function and those with moderate (P=.06 and P=.09, respectively) and good (P=.37 and P=.99, respectively) hand function. Regarding the ability of the 10 participants with poor hand function to interact with the 3 hand-based rehabilitation devices, 2 (20\%) participants with an ARAT score greater than 0 were able to interact with the devices, whereas the other 8 (80\%) who had an ARAT score of 0 could not. Their inability to interact with these devices was clinically examined, and the reason was determined to be a result of either the presence of (1) muscle tone or stiffness or (2) muscle weakness. Conclusions: Not all stroke survivors with impairments in their hands can make use of currently available rehabilitation technologies. Those with an ARAT score of 0 cannot actively interact with hand rehabilitation devices, as they cannot carry out the hand movement necessary for such interaction. The design of devices for hand rehabilitation should consider the accessibility needs of those with poor hand function. ",
doi="10.2196/54159",
url="https://biomedeng.jmir.org/2024/1/e54159",
url="http://www.ncbi.nlm.nih.gov/pubmed/38922668"
}


@Article{info:doi/10.2196/41906,
author="Caelers, Inge
and Boselie, Toon
and van Hemert, Wouter
and Rijkers, Kim
and De Bie, Rob
and van Santbrink, Henk",
title="The Variability of Lumbar Sequential Motion Patterns: Observational Study",
journal="JMIR Biomed Eng",
year="2023",
month="Jun",
day="20",
volume="8",
pages="e41906",
keywords="lumbar spine",
keywords="cinematographic recordings",
keywords="sequence",
keywords="motion pattern",
keywords="flexion",
keywords="extension",
keywords="rotation",
keywords="physiological",
keywords="musculoskeletal",
keywords="motion",
keywords="spine",
keywords="upper lumbar",
keywords="observational study",
keywords="physiological motion",
abstract="Background: Physiological motion of the lumbar spine is a topic of interest for musculoskeletal health care professionals since abnormal motion is believed to be related to lumbar complaints. Many researchers have described ranges of motion for the lumbar spine, but only few have mentioned specific motion patterns of each individual segment during flexion and extension, mostly comprising the sequence of segmental initiation in sagittal rotation. However, an adequate definition of physiological motion is still lacking. For the lower cervical spine, a consistent pattern of segmental contributions in a flexion-extension movement in young healthy individuals was described, resulting in a definition of physiological motion of the cervical spine. Objective: This study aimed to define the lumbar spines' physiological motion pattern by determining the sequence of segmental contribution in sagittal rotation of each vertebra during maximum flexion and extension in healthy male participants. Methods: Cinematographic recordings were performed twice in 11 healthy male participants, aged 18-25 years, without a history of spine problems, with a 2-week interval (time point T1 and T2). Image recognition software was used to identify specific patterns in the sequence of segmental contributions per individual by plotting segmental rotation of each individual segment against the cumulative rotation of segments L1 to S1. Intraindividual variability was determined by testing T1 against T2. Intraclass correlation coefficients were tested by reevaluation of 30 intervertebral sequences by a second researcher. Results: No consistent pattern was found when studying the graphs of the cinematographic recordings during flexion. A much more consistent pattern was found during extension, especially in the last phase. It consisted of a peak in rotation in L3L4, followed by a peak in L2L3, and finally, in L1L2. This pattern was present in 71\% (15/21) of all recordings; 64\% (7/11) of the participants had a consistent pattern at both time points. Sequence of segmental contribution was less consistent in the lumbar spine than the cervical spine, possibly caused by differences in facet orientation, intervertebral discs, overprojection of the pelvis, and muscle recruitment. Conclusions: In 64\% (7/11) of the recordings, a consistent motion pattern was found in the upper lumbar spine during the last phase of extension in asymptomatic young male participants. Physiological motion of the lumbar spine is a broad concept, influenced by multiple factors, which cannot be captured in a firm definition yet. Trial Registration: ClinicalTrials.gov NCT03737227; https://clinicaltrials.gov/ct2/show/NCT03737227 International Registered Report Identifier (IRRID): RR2-10.2196/14741 ",
doi="10.2196/41906",
url="https://biomedeng.jmir.org/2023/1/e41906",
url="http://www.ncbi.nlm.nih.gov/pubmed/38875682"
}


@Article{info:doi/10.2196/33771,
author="Lakkapragada, Anish
and Kline, Aaron
and Mutlu, Cezmi Onur
and Paskov, Kelley
and Chrisman, Brianna
and Stockham, Nathaniel
and Washington, Peter
and Wall, Paul Dennis",
title="The Classification of Abnormal Hand Movement to Aid in Autism Detection: Machine Learning Study",
journal="JMIR Biomed Eng",
year="2022",
month="Jun",
day="6",
volume="7",
number="1",
pages="e33771",
keywords="deep learning",
keywords="machine learning",
keywords="activity recognition",
keywords="applied machine learning",
keywords="landmark detection",
keywords="autism",
keywords="diagnosis",
keywords="health informatics",
keywords="detection",
keywords="feasibility",
keywords="video",
keywords="model",
keywords="neural network",
abstract="Background: A formal autism diagnosis can be an inefficient and lengthy process. Families may wait several months or longer before receiving a diagnosis for their child despite evidence that earlier intervention leads to better treatment outcomes. Digital technologies that detect the presence of behaviors related to autism can scale access to pediatric diagnoses. A strong indicator of the presence of autism is self-stimulatory behaviors such as hand flapping. Objective: This study aims to demonstrate the feasibility of deep learning technologies for the detection of hand flapping from unstructured home videos as a first step toward validation of whether statistical models coupled with digital technologies can be leveraged to aid in the automatic behavioral analysis of autism. To support the widespread sharing of such home videos, we explored privacy-preserving modifications to the input space via conversion of each video to hand landmark coordinates and measured the performance of corresponding time series classifiers. Methods: We used the Self-Stimulatory Behavior Dataset (SSBD) that contains 75 videos of hand flapping, head banging, and spinning exhibited by children. From this data set, we extracted 100 hand flapping videos and 100 control videos, each between 2 to 5 seconds in duration. We evaluated five separate feature representations: four privacy-preserved subsets of hand landmarks detected by MediaPipe and one feature representation obtained from the output of the penultimate layer of a MobileNetV2 model fine-tuned on the SSBD. We fed these feature vectors into a long short-term memory network that predicted the presence of hand flapping in each video clip. Results: The highest-performing model used MobileNetV2 to extract features and achieved a test F1 score of 84 (SD 3.7; precision 89.6, SD 4.3 and recall 80.4, SD 6) using 5-fold cross-validation for 100 random seeds on the SSBD data (500 total distinct folds). Of the models we trained on privacy-preserved data, the model trained with all hand landmarks reached an F1 score of 66.6 (SD 3.35). Another such model trained with a select 6 landmarks reached an F1 score of 68.3 (SD 3.6). A privacy-preserved model trained using a single landmark at the base of the hands and a model trained with the average of the locations of all the hand landmarks reached an F1 score of 64.9 (SD 6.5) and 64.2 (SD 6.8), respectively. Conclusions: We created five lightweight neural networks that can detect hand flapping from unstructured videos. Training a long short-term memory network with convolutional feature vectors outperformed training with feature vectors of hand coordinates and used almost 900,000 fewer model parameters. This study provides the first step toward developing precise deep learning methods for activity detection of autism-related behaviors. ",
doi="10.2196/33771",
url="https://biomedeng.jmir.org/2022/1/e33771",
url="http://www.ncbi.nlm.nih.gov/pubmed/27666281"
}


@Article{info:doi/10.2196/13611,
author="Wang, Max
and Ge, Wenbo
and Apthorp, Deborah
and Suominen, Hanna",
title="Robust Feature Engineering for Parkinson Disease Diagnosis: New Machine Learning Techniques",
journal="JMIR Biomed Eng",
year="2020",
month="Jul",
day="27",
volume="5",
number="1",
pages="e13611",
keywords="machine learning",
keywords="mobile phone",
keywords="nonlinear dynamics",
keywords="Parkinson disease",
keywords="signal processing, computer-assisted",
keywords="speech",
keywords="biomarkers",
abstract="Background: Parkinson disease (PD) is a common neurodegenerative disorder that affects between 7 and 10 million people worldwide. No objective test for PD currently exists, and studies suggest misdiagnosis rates of up to 34\%. Machine learning (ML) presents an opportunity to improve diagnosis; however, the size and nature of data sets make it difficult to generalize the performance of ML models to real-world applications. Objective: This study aims to consolidate prior work and introduce new techniques in feature engineering and ML for diagnosis based on vowel phonation. Additional features and ML techniques were introduced, showing major performance improvements on the large mPower vocal phonation data set. Methods: We used 1600 randomly selected /aa/ phonation samples from the entire data set to derive rules for filtering out faulty samples from the data set. The application of these rules, along with a joint age-gender balancing filter, results in a data set of 511 PD patients and 511 controls. We calculated features on a 1.5-second window of audio, beginning at the 1-second mark, for a support vector machine. This was evaluated with 10-fold cross-validation (CV), with stratification for balancing the number of patients and controls for each CV fold. Results: We showed that the features used in prior literature do not perform well when extrapolated to the much larger mPower data set. Owing to the natural variation in speech, the separation of patients and controls is not as simple as previously believed. We presented significant performance improvements using additional novel features (with 88.6\% certainty, derived from a Bayesian correlated t test) in separating patients and controls, with accuracy exceeding 58\%. Conclusions: The results are promising, showing the potential for ML in detecting symptoms imperceptible to a neurologist. ",
doi="10.2196/13611",
url="https://biomedeng.jmir.org/2020/1/e13611"
}


@Article{info:doi/10.2196/12291,
author="Shum, C. Leia
and Vald{\'e}s, A. Bulmaro
and Van der Loos, Machiel H. F.",
title="Determining the Accuracy of Oculus Touch Controllers for Motor Rehabilitation Applications Using Quantifiable Upper Limb Kinematics: Validation Study",
journal="JMIR Biomed Eng",
year="2019",
month="Jun",
day="06",
volume="4",
number="1",
pages="e12291",
keywords="upper extremity",
keywords="kinematics",
keywords="physical medicine and rehabilitation",
keywords="validation studies",
keywords="virtual reality",
abstract="Background: As commercial motion tracking technology becomes more readily available, it is necessary to evaluate the accuracy of these systems before using them for biomechanical and motor rehabilitation applications. Objective: This study aimed to evaluate the relative position accuracy of the Oculus Touch controllers in a 2.4 x 2.4 m play-space. Methods: Static data samples (n=180) were acquired from the Oculus Touch controllers at step sizes ranging from 5 to 500 mm along 16 different points on the play-space floor with graph paper in the x (width), y (height), and z (depth) directions. The data were compared with reference values using measurements from digital calipers, accurate to 0.01 mm; physical blocks, for which heights were confirmed with digital calipers; and for larger step sizes (300 and 500 mm), a ruler with hatch marks to millimeter units. Results: It was found that the maximum position accuracy error of the system was 3.5 {\textpm} 2.5 mm at the largest step size of 500 mm along the z-axis. When normalized to step size, the largest error found was 12.7 {\textpm} 9.9\% at the smallest step size in the y-axis at 6.23 mm. When the step size was <10 mm in any direction, the relative position accuracy increased considerably to above 2\% (approximately 2 mm at maximum). An average noise value of 0.036 mm was determined. A comparison of these values to cited visual, goniometric, and proprioceptive resolutions concludes that this system is viable for tracking upper-limb movements for biomechanical and rehabilitation applications. The accuracy of the system was also compared with accuracy values from previous studies using other commercially available devices and a multicamera, marker-based professional motion tracking system. Conclusions: The study found that the linear position accuracy of the Oculus Touch controllers was within an agreeable range for measuring human kinematics in rehabilitative upper-limb exercise protocols. Further testing is required to ascertain acceptable repeatability in multiple sessions and rotational accuracy. ",
doi="10.2196/12291",
url="http://biomedeng.jmir.org/2019/1/e12291/"
}


@Article{info:doi/10.2196/11670,
author="Hamilton, Taya
and Durand, Stan
and Krebs, Igo Hermano",
title="The Impact of Aging and Hand Dominance on the Passive Wrist Stiffness of Squash Players: Pilot Study",
journal="JMIR Biomed Eng",
year="2019",
month="May",
day="07",
volume="4",
number="1",
pages="e11670",
keywords="wrist",
keywords="exercise",
keywords="aging",
abstract="Background: Passive joint stiffness can influence the risk of injury and the ability to participate in sports and activities of daily living. However, little is known about how passive joint stiffness changes over time with intensive repetitive exercise, particularly when performing unilateral activities using the dominant upper limb. Objective: This study aimed to investigate the difference in passive wrist quasi-stiffness between the dominant and nondominant upper limb of competitive squash players, compare these results with a previous study on young unskilled subjects, and explore the impact of aging on wrist stiffness. Methods: A total of 7 healthy, right-side dominant male competitive squash players were recruited and examined using the Massachusetts Institute of Technology Wrist-Robot. Subjects were aged between 24 and 72 years (mean 43.7, SD 16.57) and had a mean of 20.6 years of squash playing experience (range 10-53 years, SD 13.85). Torque and displacement data were processed and applied to 2 different estimation methods, the fitting ellipse and the multiple regression method, to obtain wrist stiffness magnitude and orientation. Results: Young squash players (mean 30.75, SD 8.06 years) demonstrated a stiffer dominant wrist, with an average ratio of 1.51, compared with an average ratio of 1.18 in young unskilled subjects. The older squash players (mean 64.67, SD 6.35 years) revealed an average ratio of 0.86 (ie, the nondominant wrist was stiffer than the dominant wrist). There was a statistically significant difference between the magnitude of passive quasi-stiffness between the dominant and nondominant wrist of the young and older squash player groups (P=.004). Conclusions: Findings from this pilot study are novel and contribute to our understanding of the likely long-term effect of highly intensive, unilateral sports on wrist quasi-stiffness and the aging process: adults who participate in repetitive sporting exercise may experience greater joint quasi-stiffness when they are younger than 45 years and more flexibility when they are older than 60 years. ",
doi="10.2196/11670",
url="http://biomedeng.jmir.org/2019/1/e11670/"
}


@Article{info:doi/10.2196/12148,
author="Salvador Verges, {\`A}ngels
and Fern{\'a}ndez-Luque, Luis
and Yildirim, Meltem
and Salvador-Mata, Bertran
and Garcia Cuy{\`a}s, Francesc",
title="Perspectives of Orthopedic Surgeons on the Clinical Use of Bioprinted Cartilage: Qualitative Study",
journal="JMIR Biomed Eng",
year="2019",
month="Feb",
day="28",
volume="4",
number="1",
pages="e12148",
keywords="bioprinting",
keywords="orthopedic surgeons",
keywords="qualitative research",
keywords="cartilage",
keywords="expert testimony",
abstract="Background: Over the past 60 years, no technique used for treating cartilage disorders has been completely successful. Bioprinting provides a highly anticipated, novel alternative solution to this problem. However, identifying barriers to this new technology is crucial in order to overcome them when bioprinting reaches the implementation stage. This kind of research has been declared essential because clinical efficacy and safety studies alone do not always lead to successful implementation. Objective: This qualitative study aimed to explore the stance of orthopedic surgeons on the use of bioprinted cartilage grafts for cartilaginous lesions. The study sought to summarize and classify the barriers and facilitators of this technique and to identify the key factors for successful implementation of bioprinted cartilage in routine clinical practice. Methods: A qualitative thematic analysis method was used to evaluate data obtained from semistructured interviews and from focus groups. Data were collected between June 2017 and February 2018. Interviews focused on the collection of expert opinions on bioprinted cartilage. Results: The perceived barriers to the adoption of this technology were (1) awareness of a lack of information on the status and possibilities of this technology, (2) uncertainty regarding compliance with current health care regulations and policies, and (3) demands for clinical evidence. The facilitators were (1) lack of surgical alternatives, (2) the perception that research is the basis of the current health system, and (3) the hope of offering a better quality of life to patients. Conclusions: The results of this study are preliminary in nature and cannot be generalized without a broader group of participants. However, the key factors identified provide a frame of reference to help understand the challenges of bioprinted cartilage and help facilitate the transition toward its clinical use. These findings will also provide information for use at multidisciplinary meetings in scientific societies; create bridges between researchers, orthopedic surgeons, and regulators; and open a debate on the funding of this technique and the business model that needs to be developed. ",
doi="10.2196/12148",
url="http://biomedeng.jmir.org/2019/1/e12148/"
}