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Tag: mobile health
Calculate risk of stroke on Apple Watch
Read a review of our stroke app on iMedicalApps! via iMedicalApps.
Effectiveness and Limitations of Unsupervised Home-Based Balance Rehabilitation with Nintendo Wii in People with Multiple Sclerosis
Balance training represents a critical part of the rehabilitation process of individuals living with multiple sclerosis (MS) since impaired postural control is a distinctive symptom of the disease. In recent years, the use of the Nintendo Wii system has become widespread among rehabilitation specialists for this purpose, but few studies have verified the effectiveness of such an approach using quantitative measures of balance. In this study, we analyzed the postural sway features of a cohort of twenty-seven individuals with MS before and after 5 weeks of unsupervised home-based balance training with the Wii system. Center of pressure (COP) time-series were recorded using a pressure platform and processed to calculate sway area, COP path length, displacements, and velocities in mediolateral (ML) and anteroposterior (AP) directions. Although the results show a significant reduction in sway area, COP displacements, and velocity, such improvements are essentially restricted to the ML direction, as the Wii platform appears to properly stimulate the postural control system in the frontal plane but not in the sagittal one. Available Wii games, although somewhat beneficial, appear not fully suitable for rehabilitation in MS owing to scarce flexibility and adaptability to MS needs and thus specific software should be developed.
New version of MedCalc for Apple Watch
We just released a new version of our Medical for Apple Watch application!
Version 2.2 introduces new scores and tools:
- Ideal body weight calculation is now included with BMI and BSA
- Corticosteroid equivalence calculator
- CAGE questionnaire (screening of alcoholism)
- Centor Score (probability of strep pharyngitis)
Medical for Apple Watch is a great tool for physicians and medical students. Previous versions already contained several tools including:
- BMI, BSA calculation
- eGFR
- Cardiovascular scores:
ABCD2, CHA2DS2 VASc, corrected QT, HEART Score, PE probability
It is fully optimized for Watch OS2!
The price ($0.99) remains unchanged! So don’t hesitate to take a look and try by yourself by clicking here
Emergency medicine and internal medicine trainees’ smartphone use in clinical settings in the United States
Purpose:
Smartphone technology offers a multitude of applications (apps) that provide a wide range of functions for healthcare professionals. Medical trainees are early adopters of this technology, but how they use smartphones in clinical care remains unclear. Our objective was to further characterize smartphone use by medical trainees at two US academic institutions, as well as their prior training in the clinical use of smartphones.
Methods:
In 2014, we surveyed 347 internal medicine and emergency medicine resident physicians at the University of Utah and Brigham and Women’s Hospital about their smartphone use and prior training experiences. Scores (0%–100%) were calculated to assess the frequency of their use of general features (email, text) and patient-specific apps, and the results were compared according to resident level and program using the Mann-Whitney U test.
Results:
A total of 184 residents responded (response rate, 53.0%). The average score for using general features, 14.4/20 (72.2%) was significantly higher than the average score for using patient-specific features and apps, 14.1/44(33.0%; P < 0.001). The average scores for the use of general features, were significantly higher for year 3–4 residents, 15.0/20 (75.1%) than year 1–2 residents, 14.1/20 (70.5%; P=0.035), and for internal medicine residents, 14.9/20 (74.6%) in comparison to emergency medicine residents, 12.9/20 (64.3%; P = 0.001). The average score reflecting the use of patient-specific apps was significantly higher for year 3–4 residents, 16.1/44 (36.5%) than for year 1–2 residents, 13.7/44 (31.1%; P = 0.044). Only 21.7% of respondents had received prior training in clinical smartphone use.
Conclusions:
Residents used smartphones for general features more frequently than for patient-specific features, but patient-specific use increased with training. Few residents have received prior training in the clinical use of smartphones.
A Decade of Progress Using Virtual Reality for Poststroke Lower Extremity Rehabilitation: Systematic Review of the Intervention Methods
Objective
To develop a systematic review of the literature, to describe the different virtual reality (VR) interventions and interactive videogames applied to the lower extremity (LE) of stroke patients, and to analyse the results according to the most frequently used outcome measures.
Material and Methods
An electronic search of randomized trials between January 2004 and January 2014 in different databases (Medline, Cinahl, Web of Science, PEDro, and Cochrane) was carried out. Several terms (virtual reality, feedback, stroke, hemiplegia, brain injury, cerebrovascular accident, lower limb, leg, and gait) were combined, and finally 11 articles were included according to the established inclusion and exclusion criteria.
Results
The reviewed trials showed a high heterogeneity in terms of study design and assessment tools, which makes it difficult to compare and analyze the different types of interventions. However, most of them found a significant improvement on gait speed, balance and motor function, due to VR intervention.
Conclusions
Although evidence is limited, it suggests that VR intervention (more than 10 sessions) in stroke patients may have a positive impact on balance, and gait recovery. Better results were obtained when a multimodal approach, combining VR and conventional physiotherapy, was used. Flexible software seems to adapt better to patients’ requirements, allowing more specific and individual treatments.
Evaluating more naturalistic outcome measures: A 1-year smartphone study in multiple sclerosis
Objective:
In this cohort of individuals with and without multiple sclerosis (MS), we illustrate some of the novel approaches that smartphones provide to monitor patients with chronic neurologic disorders in their natural setting.
Methods:
Thirty-eight participant pairs (MS and cohabitant) aged 18–55 years participated in the study. Each participant received an Android HTC Sensation 4G smartphone containing a custom application suite of 19 tests capturing participant performance and patient-reported outcomes (PROs). Over 1 year, participants were prompted daily to complete one assigned test.
Results:
A total of 22 patients with MS and 17 cohabitants completed the entire study. Among patients with MS, low scores on PROs relating to mental and visual function were associated with dropout (p < 0.05). We illustrate several novel features of a smartphone platform. First, fluctuations in MS outcomes (e.g., fatigue) were assessed against an individual’s ambient environment by linking responses to meteorological data. Second, both response accuracy and speed for the Ishihara color vision test were captured, highlighting the benefits of both active and passive data collection. Third, a new trait, a person-specific learning curve in neuropsychological testing, was identified using spline analysis. Finally, averaging repeated measures over the study yielded the most robust correlation matrix of the different outcome measures.
Conclusions:
We report the feasibility of, and barriers to, deploying a smartphone platform to gather useful passive and active performance data at high frequency in an unstructured manner in the field. A smartphone platform may therefore enable large-scale naturalistic studies of patients with MS or other neurologic diseases.
Apple: ResearchKit is a pipeline for future diagnostic medical apps
“One way to think about ResearchKit is as the beginning of a pipeline that will lead to more apps that are screening, diagnostic, management and treatment apps,” Bud Tribble, MD, PhD, Vice President of Software Technology at Apple said. “In fact, it is a necessary, essential first step to figure out what is needed to develop these apps — what works and what doesn’t — before you move into, ultimately, clinical study apps and clearance to use them for diagnosis and treatment.”
Read the full article for a review of current ResearchKit apps and perspectives…
via MobiHealthNews.
Discover the most powerful medical calculator available on Apple Watch
Development and Evaluation of an Evaluation Tool for Healthcare Smartphone Applications
Introduction: Various types of healthcare smartphone applications (apps) have been released in recent years, making it possible for people to manage their health anytime and anywhere. As a healthcare provider, who has the responsibility to provide guidance as to which apps can be used? The purpose of this study was to develop and evaluate an evaluation tool for the various aspects of healthcare smartphone apps.
Materials and Methods: In the first phase, a provisional version of an evaluation tool for healthcare smartphone apps was developed from a review of previous studies. In the second phase, the provisional tool was modified and edited after verification by five experts with regard to its content validity. In the third phase, from September 25 to October 4, 2013, 200 responses were collected to verify the construct validity and reliability of the tool.
Results: The edited tool had 23 evaluating items with three evaluating factors along with seven subevaluating factors as a result of confirmatory factor analysis. The reliability was found to be high (0.905).
Conclusions: This study is meaningful because it demonstrates a healthcare smartphone app evaluation tool that is proven in terms of its validity and reliability. The evaluation tool developed and tested in this study is an appropriate and widely applicable tool with which to evaluate healthcare smartphone apps to determine if they are reliable and useful. However, this evaluation tool represents the beginning of the research in this area.
MiKe iOS Applications 