JMIR Medical Informatics

Clinical informatics, decision support for health professionals, electronic health records, and ehealth infrastructures.

Mobile Jump Assessment (mJump): a descriptive and inferential study.

Background: Background: Vertical jump tests are used to estimate different qualities in people of different age ranges and fitness. Jumping ability can be analysed through different variables, they can be obtained by a variety of measuring devices, most limited to laboratory use only. The current generation of smartphones contains inertial sensors that can be able to record kinematic variables for the human motion analysis, being tools for easy access and portability for clinical use. Objective: Objective: The aim of this study was to describe and analyze the kinematics characteristics using the inertial sensor incorporated in the iPhone 4S®, the lower limbs strength through a manual dynamometer and the jump variables obtained with a contact mat in the Squat Jump and Countermovement Jump tests from a cohort of healthy people. Methods: Methods: A cross sectional study was conducted on a population of healthy young adults. 27 participants performed 3 trials (n=81 jumps) of Squat Jump and Countermovement Jump tests. Though a smartphone´s inertial sensor acceleration variables was measured. Besides, jump variables from a contact mat and lower limbs dynamometry was collected. Results: Results: In the present study the kinematic variables derived from acceleration through the inertial sensor of a smartphone iPhone 4S®, dynamometry of lower limbs with a handheld dynamometer and the height and flight time with a contact mat have been described in vertical jump tests from a cohort of young healthy subjects. Has been described, examined and identified the development of the execution in Squat Jump and Countermovement Jump vertical jump test under acceleration variables obtained with the smartphone. Conclusions: Conclusions: According to the results obtained in this study, we can conclude that the built-in iPhone 4S® inertial sensor is able to measure acceleration variables while performing vertical jump tests Squat Jump and Countermovement Jump in healthy young adults. The acceleration kinematics variables derivate from smartphone´s inertial sensor are higher in the Countermovement Jump test than Squat Jump test.

2014-10-27

The paper “Bridging Organizational Divides in Health Care: An Ecological View of Health Information Exchange” published in the first issue of the new JMIR Medical Informatics journal, is a finalist for the Diana Forsythe Award from the People and Organizational Issues Working Group of AMIA. The award "honors a paper that best exemplifies the spirit and scholarship of Diana Forsythe’s work at the intersection of informatics and social sciences.” The award will be given at the closing session for AMIA in November 2014. "Just being a finalist is a huge honor because it is a highly competitive pool of papers.", says lead author Kim Unertl, Assistant Professor at the Department of Biomedical Informatics, Vanderbilt University. "The online format of JMIR Medical Informatics played a huge role in the final quality of this paper, because making the content fit within the word limits of many print journals would have been challenging and would have required fundamentally altering the direction and content of the paper.". JMIR Medical Informatics is a new sister journal of JMIR, the worlds' leading ehealth journal.

Read Post

Journal Description

JMIR Medical Informatics (JMI, ISSN 2291-9694) focusses on clinical informatics, big data in health and health care, decision support for health professionals, electronic health records, ehealth infrastructures and implementation. It has a focus on applied, translational research, with a broad readership including clinicians, CIOs, engineers, industry and health informatics professionals.

Published by JMIR Publications, publisher of the Journal of Medical Internet Research (JMIR), the leading eHealth/mHealth journal (Impact Factor 2013: 4.7), JMIR Med Inform has a different scope (emphasizing more on applications for clinicians and health professionals rather than consumers/citizens, which is the focus of JMIR), publishes even faster, and also allows papers which are more technical or more formative than what would be published in the Journal of Medical Internet Research.

JMIR Medical Informatics journal features a rapid and thorough peer-review process, professional copyediting, professional production of PDF, XHTML, and XML proofs (ready for deposit in PubMed Central/PubMed). The site is optimized for mobile and iPad use.

JMIR Medical Informatics adheres to the same quality standards as JMIR and all articles published here are also cross-listed in the Table of Contents of JMIR, the worlds' leading medical journal in health sciences / health services research and health informatics (http://www.jmir.org/issue/current).

 

Recent Articles:

  • Metadata Correction: Making Big Data Useful for Health Care: A Summary of the Inaugural MIT Critical Data Conference

    Abstract:

    See Manuscript File

  • This is a royalty free image by Ambro (http://www.freedigitalphotos.net/images/Healthcare_g355-General_Practitioner_p38464.html).

    Veteran, Primary Care Provider, and Specialist Satisfaction With Electronic Consultation

    Abstract:

    Background: Access to specialty care is challenging for veterans in rural locations. To address this challenge, in December 2009, the Veterans Affairs (VA) Pittsburgh Healthcare System (VAPHS) implemented an electronic consultation (e-consult) program to provide primary care providers (PCPs) and patients with enhanced specialty care access. Objective: The aim of this quality improvement (QI) project evaluation was to: (1) assess satisfaction with the e-consult process, and (2) identify perceived facilitators and barriers to using the e-consult program. Methods: We conducted semistructured telephone interviews with veteran patients (N=15), Community Based Outpatient Clinic (CBOC) PCPs (N=15), and VA Pittsburgh specialty physicians (N=4) who used the e-consult program between December 2009 to August 2010. Participants answered questions regarding satisfaction in eight domains and identified factors contributing to their responses. Results: Most participants were white (patients=87%; PCPs=80%; specialists=75%) and male (patients=93%; PCPs=67%; specialists=75%). On average, patients had one e-consult (SD 0), PCPs initiated 6 e-consults (SD 6), and VAPHS specialists performed 17 e-consults (SD 11). Patients, PCPs, and specialty physicians were satisfied with e-consults median (range) of 5.0 (4-5) on 1-5 Likert-scale, 4.0 (3-5), and 3.5 (3-5) respectively. The most common reason why patients and specialists reported increased overall satisfaction with e-consults was improved communication, whereas improved timeliness of care was the most common reason for PCPs. Communication was the most reported perceived barrier and facilitator to e-consult use. Conclusions: Veterans and VA health care providers were satisfied with the e-consult process. Our findings suggest that while the reasons for satisfaction with e-consult differ somewhat for patients and physicians, e-consult may be a useful tool to improve VA health care system access for rural patients.

  • Dynamic consent interface. The origin of the image is from HW Communications and the University of Oxford.

    Dynamic Consent: A Possible Solution to Improve Patient Confidence and Trust in How Electronic Patient Records Are Used in Medical Research

    Abstract:

    With one million people treated every 36 hours, routinely collected UK National Health Service (NHS) health data has huge potential for medical research. Advances in data acquisition from electronic patient records (EPRs) means such data are increasingly digital and can be anonymised for research purposes. NHS England’s care.data initiative recently sought to increase the amount and availability of such data. However, controversy and uncertainty following the care.data public awareness campaign led to a delay in rollout, indicating that the success of EPR data for medical research may be threatened by a loss of patient and public trust. The sharing of sensitive health care data can only be done through maintaining such trust in a constantly evolving ethicolegal and political landscape. We propose that a dynamic consent model, whereby patients can electronically control consent through time and receive information about the uses of their data, provides a transparent, flexible, and user-friendly means to maintain public trust. This could leverage the huge potential of the EPR for medical research and, ultimately, patient and societal benefit.

  • TOC image
http://www.istockphoto.com/photo/e-health-data-link-40258008?st=7e2178d
paid the 1 credit cost to iStock.

    Impact of Information Technology on Information Gaps in Canadian Ambulatory Care Encounters

    Abstract:

    Background: Specialist physicians require clinical information for patient visits in ambulatory encounters, some of which they may access via digital health solutions. Objective: This study explored the completeness of information for patient care and the consequences of gaps for ambulatory specialist services provided in ambulatory settings in Canada. Methods: A sample of specialist physicians practising in outpatient clinics was recruited from a health care provider research panel. The study (n=1800 patient encounters) looked at the completeness of patient information experienced by physicians who work in environments with rich health information exchange (Connected) and a comparison cohort with less information available electronically (Unconnected). Results: Unconnected physicians were significantly more likely to be missing information they needed for patient encounters (13% of encounters for Unconnected physicians vs 7% for Connected physicians). Unconnected physicians were also more likely to report that missing information had consequences (23% vs 13% of encounters). Lab results were the most common type of patient information missing for both Unconnected and Connected specialists (25% for Unconnected physicians vs 11% Connected physicians). Conclusions: The results from this study indicate that Canadian physicians commonly experience information gaps in ambulatory encounters, and that many of these gaps are of consequence to themselves, their patients, and the healthcare system. Wasting physician and patient time, as well as being forced to proceed with incomplete information, were the most common consequences of information gaps reported.

  • License to use purchased from http://www.istockphoto.com/.

    Adoption of Clinical Decision Support in Multimorbidity: A Systematic Review

    Abstract:

    Background: Patients with multiple conditions have complex needs and are increasing in number as populations age. This multimorbidity is one of the greatest challenges facing health care. Having more than 1 condition generates (1) interactions between pathologies, (2) duplication of tests, (3) difficulties in adhering to often conflicting clinical practice guidelines, (4) obstacles in the continuity of care, (5) confusing self-management information, and (6) medication errors. In this context, clinical decision support (CDS) systems need to be able to handle realistic complexity and minimize iatrogenic risks. Objective: The aim of this review was to identify to what extent CDS is adopted in multimorbidity. Methods: This review followed PRISMA guidance and adopted a multidisciplinary approach. Scopus and PubMed searches were performed by combining terms from 3 different thesauri containing synonyms for (1) multimorbidity and comorbidity, (2) polypharmacy, and (3) CDS. The relevant articles were identified by examining the titles and abstracts. The full text of selected/relevant articles was analyzed in-depth. For articles appropriate for this review, data were collected on clinical tasks, diseases, decision maker, methods, data input context, user interface considerations, and evaluation of effectiveness. Results: A total of 50 articles were selected for the full in-depth analysis and 20 studies were included in the final review. Medication (n=10) and clinical guidance (n=8) were the predominant clinical tasks. Four studies focused on merging concurrent clinical practice guidelines. A total of 17 articles reported their CDS systems were knowledge-based. Most articles reviewed considered patients’ clinical records (n=19), clinical practice guidelines (n=12), and clinicians’ knowledge (n=10) as contextual input data. The most frequent diseases mentioned were cardiovascular (n=9) and diabetes mellitus (n=5). In all, 12 articles mentioned generalist doctor(s) as the decision maker(s). For articles reviewed, there were no studies referring to the active involvement of the patient in the decision-making process or to patient self-management. None of the articles reviewed adopted mobile technologies. There were no rigorous evaluations of usability or effectiveness of the CDS systems reported. Conclusions: This review shows that multimorbidity is underinvestigated in the informatics of supporting clinical decisions. CDS interventions that systematize clinical practice guidelines without considering the interactions of different conditions and care processes may lead to unhelpful or harmful clinical actions. To improve patient safety in multimorbidity, there is a need for more evidence about how both conditions and care processes interact. The data needed to build this evidence base exist in many electronic health record systems and are underused.

  • E-prescribing. Image Source: Jupiterimages/Gettyimages http://www.gettyimages.com/detail/photo/pharmacist-with-pill-bottles-at-computer-royalty-free-image/86530681.

    Impact of Early Electronic Prescribing on Pharmacists’ Clarification Calls in Four Community Pharmacies Located in St John’s, Newfoundland

    Abstract:

    Background: Electronic prescribing (e-prescribing) can potentially help prevent medication errors. As the use of e-prescribing increases across Canada, understanding the benefits and gaps of early e-prescribing can help inform deployment of future e-prescribing systems. Objective: The purpose of this exploratory study was to determine the prevalence of, reasons for, and average time taken for pharmacist clarification calls to prescribers for electronic medical record (EMR)-generated and handwritten prescriptions. Methods: Four community pharmacies in St John’s, Newfoundland, Canada prospectively collected information on clarification calls to prescribers for new prescriptions over a period of 17 to 19 weeks. Four semistructured interviews were conducted following the data collection period to gain further insight. Results: An estimated 1.33% of handwritten prescriptions required clarification compared with 0.66% of EMR-generated prescriptions. Overall, 1.11% of prescriptions required clarification with the prescriber. While illegibility was eliminated with EMR-generated prescriptions, clarification was still required for missing information (24%) and appropriateness (51%). Key themes, including errors unique to EMR-generated prescriptions, emerged from the qualitative interviews. Conclusions: Advanced e-prescribing functionality will enable secure transmission of prescriptions from prescribers to a patient’s pharmacy of choice through a provincial electronic Drug Information System (DIS)/Pharmacy Network, which will lessen the need for clarification calls, especially in the domains of missing information and appropriateness of the prescription. This exploratory study provides valuable insight into the benefits and gaps of early e-prescribing. Advanced e-prescribing systems will provide an opportunity for further realization of quality and safety benefits related to medication prescribing.

  • URL: http://pixabay.com 
License: Creative Commons Deed CC0 - http://pixabay.com/en/service/terms/#download_terms.

    CohortExplorer: A Generic Application Programming Interface for Entity Attribute Value Database Schemas

    Abstract:

    Background: Most electronic data capture (EDC) and electronic data management (EDM) systems developed to collect and store clinical data from participants recruited into studies are based on generic entity-attribute-value (EAV) database schemas which enable rapid and flexible deployment in a range of study designs. The drawback to such schemas is that they are cumbersome to query with structured query language (SQL). The problem increases when researchers involved in multiple studies use multiple electronic data capture and management systems each with variation on the EAV schema. Objective: The aim of this study is to develop a generic application which allows easy and rapid exploration of data and metadata stored under EAV schemas that are organized into a survey format (questionnaires/events, questions, values), in other words, the Clinical Data Interchange Standards Consortium (CDISC) Observational Data Model (ODM). Methods: CohortExplorer is written in Perl programming language and uses the concept of SQL abstract which allows the SQL query to be treated like a hash (key-value pairs). Results: We have developed a tool, CohortExplorer, which once configured for a EAV system will "plug-n-play" with EAV schemas, enabling the easy construction of complex queries through an abstracted interface. To demonstrate the utility of the CohortExplorer system, we show how it can be used with the popular EAV based frameworks; Opal (OBiBa) and REDCap. Conclusions: The application is available under a GPL-3+ license at the CPAN website. Currently the application only provides datasource application programming interfaces (APIs) for Opal and REDCap. In the future the application will be available with datasource APIs for all major electronic data capture and management systems such as OpenClinica and LabKey. At present the application is only compatible with EAV systems where the metadata is organized into surveys, questionnaires and events. Further work is needed to make the application compatible with EAV schemas where the metadata is organized into hierarchies such as Informatics for Integrating Biology & the Bedside (i2b2). A video tutorial demonstrating the application setup, datasource configuration, and search features is available on YouTube. The application source code is available at the GitHub website and the users are encouraged to suggest new features and contribute to the development of APIs for new EAV systems.

  • An effective search engine to find physicians’ information is a critical but often lacking function of a healthcare provider’s website. The Fuzzy-Match Search Engine for Physician Directories overcomes the limitations faced by search engines.

    A Fuzzy-Match Search Engine for Physician Directories

    Abstract:

    Background: A search engine to find physicians’ information is a basic but crucial function of a health care provider’s website. Inefficient search engines, which return no results or incorrect results, can lead to patient frustration and potential customer loss. A search engine that can handle misspellings and spelling variations of names is needed, as the United States (US) has culturally, racially, and ethnically diverse names. Objective: The Marshfield Clinic website provides a search engine for users to search for physicians’ names. The current search engine provides an auto-completion function, but it requires an exact match. We observed that 26% of all searches yielded no results. The goal was to design a fuzzy-match algorithm to aid users in finding physicians easier and faster. Methods: Instead of an exact match search, we used a fuzzy algorithm to find similar matches for searched terms. In the algorithm, we solved three types of search engine failures: “Typographic”, “Phonetic spelling variation”, and “Nickname”. To solve these mismatches, we used a customized Levenshtein distance calculation that incorporated Soundex coding and a lookup table of nicknames derived from US census data. Results: Using the “Challenge Data Set of Marshfield Physician Names,” we evaluated the accuracy of fuzzy-match engine–top ten (90%) and compared it with exact match (0%), Soundex (24%), Levenshtein distance (59%), and fuzzy-match engine–top one (71%). Conclusions: We designed, created a reference implementation, and evaluated a fuzzy-match search engine for physician directories. The open-source code is available at the codeplex website and a reference implementation is available for demonstration at the datamarsh website.

  • Location-based visualization of HIV prevalence in sub-Saharan Africa. The health-related data and the time series graph are displayed by clicking on the map of the country.

    Design and Development of a Linked Open Data-Based Health Information Representation and Visualization System: Potentials and Preliminary Evaluation

    Abstract:

    Background: Healthcare organizations around the world are challenged by pressures to reduce cost, improve coordination and outcome, and provide more with less. This requires effective planning and evidence-based practice by generating important information from available data. Thus, flexible and user-friendly ways to represent, query, and visualize health data becomes increasingly important. International organizations such as the World Health Organization (WHO) regularly publish vital data on priority health topics that can be utilized for public health policy and health service development. However, the data in most portals is displayed in either Excel or PDF formats, which makes information discovery and reuse difficult. Linked Open Data (LOD)—a new Semantic Web set of best practice of standards to publish and link heterogeneous data—can be applied to the representation and management of public level health data to alleviate such challenges. However, the technologies behind building LOD systems and their effectiveness for health data are yet to be assessed. Objective: The objective of this study is to evaluate whether Linked Data technologies are potential options for health information representation, visualization, and retrieval systems development and to identify the available tools and methodologies to build Linked Data-based health information systems. Methods: We used the Resource Description Framework (RDF) for data representation, Fuseki triple store for data storage, and Sgvizler for information visualization. Additionally, we integrated SPARQL query interface for interacting with the data. We primarily use the WHO health observatory dataset to test the system. All the data were represented using RDF and interlinked with other related datasets on the Web of Data using Silk—a link discovery framework for Web of Data. A preliminary usability assessment was conducted following the System Usability Scale (SUS) method. Results: We developed an LOD-based health information representation, querying, and visualization system by using Linked Data tools. We imported more than 20,000 HIV-related data elements on mortality, prevalence, incidence, and related variables, which are freely available from the WHO global health observatory database. Additionally, we automatically linked 5312 data elements from DBpedia, Bio2RDF, and LinkedCT using the Silk framework. The system users can retrieve and visualize health information according to their interests. For users who are not familiar with SPARQL queries, we integrated a Linked Data search engine interface to search and browse the data. We used the system to represent and store the data, facilitating flexible queries and different kinds of visualizations. The preliminary user evaluation score by public health data managers and users was 82 on the SUS usability measurement scale. The need to write queries in the interface was the main reported difficulty of LOD-based systems to the end user. Conclusions: The system introduced in this article shows that current LOD technologies are a promising alternative to represent heterogeneous health data in a flexible and reusable manner so that they can serve intelligent queries, and ultimately support decision-making. However, the development of advanced text-based search engines is necessary to increase its usability especially for nontechnical users. Further research with large datasets is recommended in the future to unfold the potential of Linked Data and Semantic Web for future health information systems development.

  • (cc) Burgos et al. CC-BY-SA 2.0, please cite as (http://medinform.jmir.org/article/viewFile/3179/1/45698).

    Clinical Decision Support System to Enhance Quality Control of Spirometry Using Information and Communication Technologies

    Abstract:

    Background: We recently demonstrated that quality of spirometry in primary care could markedly improve with remote offline support from specialized professionals. It is hypothesized that implementation of automatic online assessment of quality of spirometry using information and communication technologies may significantly enhance the potential for extensive deployment of a high quality spirometry program in integrated care settings. Objective: The objective of the study was to elaborate and validate a Clinical Decision Support System (CDSS) for automatic online quality assessment of spirometry. Methods: The CDSS was done through a three step process including: (1) identification of optimal sampling frequency; (2) iterations to build-up an initial version using the 24 standard spirometry curves recommended by the American Thoracic Society; and (3) iterations to refine the CDSS using 270 curves from 90 patients. In each of these steps the results were checked against one expert. Finally, 778 spirometry curves from 291 patients were analyzed for validation purposes. Results: The CDSS generated appropriate online classification and certification in 685/778 (88.1%) of spirometry testing, with 96% sensitivity and 95% specificity. Conclusions: Consequently, only 93/778 (11.9%) of spirometry testing required offline remote classification by an expert, indicating a potential positive role of the CDSS in the deployment of a high quality spirometry program in an integrated care setting.

  • Clinical Data Miner (CDM)'s data collection user interface. The possibility to include pictograms in case report forms is particularly interesting for variables obtained from imaging modalities.

    Clinical Data Miner: An Electronic Case Report Form System With Integrated Data Preprocessing and Machine-Learning Libraries Supporting Clinical Diagnostic...

    Abstract:

    Background: Using machine-learning techniques, clinical diagnostic model research extracts diagnostic models from patient data. Traditionally, patient data are often collected using electronic Case Report Form (eCRF) systems, while mathematical software is used for analyzing these data using machine-learning techniques. Due to the lack of integration between eCRF systems and mathematical software, extracting diagnostic models is a complex, error-prone process. Moreover, due to the complexity of this process, it is usually only performed once, after a predetermined number of data points have been collected, without insight into the predictive performance of the resulting models. Objective: The objective of the study of Clinical Data Miner (CDM) software framework is to offer an eCRF system with integrated data preprocessing and machine-learning libraries, improving efficiency of the clinical diagnostic model research workflow, and to enable optimization of patient inclusion numbers through study performance monitoring. Methods: The CDM software framework was developed using a test-driven development (TDD) approach, to ensure high software quality. Architecturally, CDM’s design is split over a number of modules, to ensure future extendability. Results: The TDD approach has enabled us to deliver high software quality. CDM’s eCRF Web interface is in active use by the studies of the International Endometrial Tumor Analysis consortium, with over 4000 enrolled patients, and more studies planned. Additionally, a derived user interface has been used in six separate interrater agreement studies. CDM's integrated data preprocessing and machine-learning libraries simplify some otherwise manual and error-prone steps in the clinical diagnostic model research workflow. Furthermore, CDM's libraries provide study coordinators with a method to monitor a study's predictive performance as patient inclusions increase. Conclusions: To our knowledge, CDM is the only eCRF system integrating data preprocessing and machine-learning libraries. This integration improves the efficiency of the clinical diagnostic model research workflow. Moreover, by simplifying the generation of learning curves, CDM enables study coordinators to assess more accurately when data collection can be terminated, resulting in better models or lower patient recruitment costs.

  • Top diseases related to adenocarcinoma of lung by onGrid (δ = 1.1).

    Enabling Online Studies of Conceptual Relationships Between Medical Terms: Developing an Efficient Web Platform

    Abstract:

    Background: The Unified Medical Language System (UMLS) contains many important ontologies in which terms are connected by semantic relations. For many studies on the relationships between biomedical concepts, the use of transitively associated information from ontologies and the UMLS has been shown to be effective. Although there are a few tools and methods available for extracting transitive relationships from the UMLS, they usually have major restrictions on the length of transitive relations or on the number of data sources. Objective: Our goal was to design an efficient online platform that enables efficient studies on the conceptual relationships between any medical terms. Methods: To overcome the restrictions of available methods and to facilitate studies on the conceptual relationships between medical terms, we developed a Web platform, onGrid, that supports efficient transitive queries and conceptual relationship studies using the UMLS. This framework uses the latest technique in converting natural language queries into UMLS concepts, performs efficient transitive queries, and visualizes the result paths. It also dynamically builds a relationship matrix for two sets of input biomedical terms. We are thus able to perform effective studies on conceptual relationships between medical terms based on their relationship matrix. Results: The advantage of onGrid is that it can be applied to study any two sets of biomedical concept relations and the relations within one set of biomedical concepts. We use onGrid to study the disease-disease relationships in the Online Mendelian Inheritance in Man (OMIM). By crossvalidating our results with an external database, the Comparative Toxicogenomics Database (CTD), we demonstrated that onGrid is effective for the study of conceptual relationships between medical terms. Conclusions: onGrid is an efficient tool for querying the UMLS for transitive relations, studying the relationship between medical terms, and generating hypotheses.

Citing this Article

Right click to copy or hit: ctrl+c (cmd+c on mac)

Latest Submissions Open for Peer-Review:

View All Open Peer Review Articles
  • Mobile Jump Assessment (mJump): a descriptive and inferential study.

    Date Submitted: Dec 8, 2014

    Open Peer Review Period: Dec 8, 2014 - Feb 2, 2015

    Background: Background: Vertical jump tests are used to estimate different qualities in people of different age ranges and fitness. Jumping ability can be analysed through different variables, they ca...

    Background: Background: Vertical jump tests are used to estimate different qualities in people of different age ranges and fitness. Jumping ability can be analysed through different variables, they can be obtained by a variety of measuring devices, most limited to laboratory use only. The current generation of smartphones contains inertial sensors that can be able to record kinematic variables for the human motion analysis, being tools for easy access and portability for clinical use. Objective: Objective: The aim of this study was to describe and analyze the kinematics characteristics using the inertial sensor incorporated in the iPhone 4S®, the lower limbs strength through a manual dynamometer and the jump variables obtained with a contact mat in the Squat Jump and Countermovement Jump tests from a cohort of healthy people. Methods: Methods: A cross sectional study was conducted on a population of healthy young adults. 27 participants performed 3 trials (n=81 jumps) of Squat Jump and Countermovement Jump tests. Though a smartphone´s inertial sensor acceleration variables was measured. Besides, jump variables from a contact mat and lower limbs dynamometry was collected. Results: Results: In the present study the kinematic variables derived from acceleration through the inertial sensor of a smartphone iPhone 4S®, dynamometry of lower limbs with a handheld dynamometer and the height and flight time with a contact mat have been described in vertical jump tests from a cohort of young healthy subjects. Has been described, examined and identified the development of the execution in Squat Jump and Countermovement Jump vertical jump test under acceleration variables obtained with the smartphone. Conclusions: Conclusions: According to the results obtained in this study, we can conclude that the built-in iPhone 4S® inertial sensor is able to measure acceleration variables while performing vertical jump tests Squat Jump and Countermovement Jump in healthy young adults. The acceleration kinematics variables derivate from smartphone´s inertial sensor are higher in the Countermovement Jump test than Squat Jump test.