Dexterity: A MATLAB-based analysis software suite for processing and visualizing data from tasks that measure arm or forelimb function.
Dexterity: A MATLAB-based analysis software suite for processing and visualizing data from tasks that measure arm or forelimb function.
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DOI：
10.1016/j.jneumeth.2017.06.002
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发表时间：
2017-07-15
影响因子：
3
通讯作者：
Carmel JB
中科院分区：
文献类型：
--
作者：
Butensky SD;Sloan AP;Meyers E;Carmel JB
手的功能是独立的关键，神经损伤往往损害灵巧性。为了测量人的手部功能或动物的前肢功能，传感器被用来量化操作。这些传感器使评估更容易，更定量，并允许这些任务的自动化。虽然自动化任务提高了客观性和吞吐量，但它们也会产生大量的数据，这些数据可能会给分析带来负担。我们开发了一款名为Dexterity的软件，可以简化自动送达任务的数据分析。灵巧是MATLAB软件，可以快速分析前肢任务的数据。通过图形用户界面，文件被加载，数据被识别和分析。可以直接对这些数据进行注释或绘图。保存分析结果，并可导出图形和相应数据。对于其他分析，Dexterity提供了对其他用户创建的自定义脚本的访问。为了确定灵巧性的效用，我们进行了一项研究，以评估任务难度对损伤后损伤程度的影响。Dexterity分析了两个月的数据，并允许新用户注释实验，可视化结果，并轻松保存和导出数据。以前的任务分析是通过自定义数据分析执行的，需要分析软件的专业知识。灵巧使得分析、可视化和注释数据所需的工具很容易被没有数据科学经验的调查人员使用。灵活性增加了自动化任务的可访问性，通过直观、健壮和高效地分析大数据来衡量灵活性。
Hand function is critical for independence, and neurological injury often impairs dexterity. To measure hand function in people or forelimb function in animals, sensors are employed to quantify manipulation. These sensors make assessment easier and more quantitative and allow automation of these tasks. While automated tasks improve objectivity and throughput, they also produce large amounts of data that can be burdensome to analyze. We created software called Dexterity that simplifies data analysis of automated reaching tasks. Dexterity is MATLAB software that enables quick analysis of data from forelimb tasks. Through a graphical user interface, files are loaded and data are identified and analyzed. These data can be annotated or graphed directly. Analysis is saved, and the graph and corresponding data can be exported. For additional analysis, Dexterity provides access to custom scripts created by other users. To determine the utility of Dexterity, we performed a study to evaluate the effects of task difficulty on the degree of impairment after injury. Dexterity analyzed two months of data and allowed new users to annotate the experiment, visualize results, and save and export data easily. Previous analysis of tasks was performed with custom data analysis, requiring expertise with analysis software. Dexterity made the tools required to analyze, visualize and annotate data easy to use by investigators without data science experience. Dexterity increases accessibility to automated tasks that measure dexterity by making analysis of large data intuitive, robust, and efficient.
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影响因子：
5.3
作者：
Brus-Ramer, Marcel;Carmel, Jason B.;Martin, John H.
通讯作者：
Martin, John H.
影响因子：
3
作者：
Ballermann, M;Metz, GAS;Whishaw, IQ
通讯作者：
Whishaw, IQ
影响因子：
3.7
作者：
Sloan, Andrew M.;Fink, Melyssa K.;Hays, Seth A.
通讯作者：
Hays, Seth A.
影响因子：
7.4
作者：
SAVITZKY, A;GOLAY, MJE
通讯作者：
GOLAY, MJE
DOI：
10.1523/jneurosci.1435-10.2010
发表时间：
2010-08-11
期刊：
The Journal of neuroscience : the official journal of the Society for Neuroscience
影响因子：
--
作者：
Carmel JB;Berrol LJ;Brus-Ramer M;Martin JH
通讯作者：
Martin JH