Keystroke timing and pressure data captured during touchscreen typing by early Parkinson's disease patients and healthy controls

DATASET The present dataset comprises keystroke timing and pressure data that correspond to short text excerpts typed by early Parkinson’s disease (PD) patients (n=18) and healthy controls (n=15) on a common touchscreen-equipped smartphone (LG Nexus 5X with a screen of 5.2 inches in diagonal and a resolution of 1080 × 1920 pixels, running native Android 7.0). Subjects were asked to transcribe up to 11 short text excerpts, with the initial one being 200 characters-long and common for all subjects, while the rest were 40-115 characters-long, pseudorandomly drawn from the fairy tale 'The Little Prince'. Data were recorded using a custom Android Operating System input method (keyboard), developed for the purposes of the study. Additional details on exepriment design, material and methods can be found in the related research article mentioned below. Data consist of sequences of raw press and release timestamps (in milliseconds), as well as of values of normalized pressure (0.000-1.000) applied to initiate keystrokes, corresponding to the consecutive keys tapped during the transcription of each text excerpt. Data included in the 'Data' folder are organised in sub-folders per subject. Each sub-folder contains a number of .txt files with each one corresponding to a text excerpt typed by the particular subject. Files are named using the format S##_TEX##.txt, with S## denoting the subject's coded ID and TEX## the serial number of the transcribed text excerpt. For all subjects, file S##_TEX01.txt corresponds to the initial and common 200 characters-long text excerpt. Each file contains the sequences of raw key press/release timestamps (Tp#, Tp#) and normalized pressure (NP#), applied to initiate each keystroke, in the following format: { Press, Tp1, Release, Tr1, NP1 Press, Tp2, Release, Tr2, NP2 . . . Press, Tpn, Release, Trn, NPn } where 1,2,...,n denote the serial index of the key tapped during typing. Note: Out of 33 subjects, 32 managed to transcribe 8 to 11 text excerpts, while the remaining one (Subject ID: 16) typed only 5. Ten subjects (Subject IDs: 6, 14, 16, 17, 25, 27, 29, 31, 32, 33) did not manage to type the initial 200 characters-long excerpt in its entirety. The dataset also includes a record, in Microsoft Excel format (Demographics_Clinical_Characteristics.xlsx), of the demographic and clinical characteristics (with respect to PD) of subjects. Entries of the Excel file are linked to subjects' sub-folders and individual keystroke data text files via the coded ID of the subject. Demographic characteristics included: Age; Gender; Education level; Years of smartphone usage; Dominant hand1 Clinical characteristics included: Group (PD, Control); Years from diagnosis; Hoehn-Yahr disease stage; Most affected side2; Levodopa Equivalent Daily Dose; UPDRS_III3 total score; UPDRS_III Item 21 Tremor-Right hand; UPDRS_III Item 21 Tremor-Left hand; UPDRS_III Item 22 Rigidity-Right hand; UPDRS_III Item 22 Rigidity-Left hand; UPDRS_III Item 23 Finger taps-Right hand; UPDRS_III Item 23 Finger taps-Left hand; UPDRS_III Item 31 Body bradykinesia/ Hypokinesia 1Dominant hand: (Relating to handedness) the operant hand generally used for performing fine motor-skills tasks. 2Most affected body side by Parkinson's disease 3UPDRS_III: Unified Parkinson's Disease Rating Scale Part III (Motor section) RELATED RESEARCH This dataset was originally used and described in the OPEN ACCESS publication: [1] Iakovakis, D., Hadjidimitriou, S., Charisis, V., Bostantzopoulou, S., Katsarou, Z., & Hadjileontiadis, L. J. (2018). Touchscreen typing-pattern analysis for detecting fine motor skills decline in early-stage Parkinson’s disease. Scientific reports, 8(1), 7663. https://doi.org/10.1038/s41598-018-25999-0 All documents and papers that report on research that uses this dataset will acknowledge this by citing the above publication. ETHICS & FUNDING The study during which the present dataset was collected was approved by the Aristotle University of Thessaloniki Bioethics Committee of Medical School (approval no. 359/3.4.17), Thessaloniki, Greece. Informed consent, including permission for third-party access to pseudo-anonymised data, was obtained from all subjects prior to their engagement with the study. The work has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No 690494 - i-PROGNOSIS: Intelligent Parkinson early detection guiding novel supportive interventions (i-prognosis.eu). CORRESPONDANCE Any inquiries regarding this dataset should be adressed to: Mr. Dimitrios Iakovakis (Electrical & Computer Engineer, PhD candidate) Signal Processing & Biomedical Technology Unit Department of Electrical & Computer Engineering Aristotle University of Thessaloniki University Campus, Building D, 6th floor Thessaloniki, Greece, GR54124 Tel: [phone] Fax: [phone] E-mail: [e-mail] LICENSE This is an open access dataset, licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). WARRANTY This dataset comes without any warranty. Administrators of this dataset can not be held accountable for any damage (physical, financial or otherwise) caused by the use of this dataset.

数据集
本数据集涵盖早期帕金森病（Parkinson’s disease, PD）患者（n=18）与健康对照者（n=15）在配备触摸屏的智能手机（LG Nexus 5X，屏幕对角线尺寸5.2英寸，分辨率1080×1920像素，运行原生安卓7.0系统）上打字产生的按键时序与压力数据。受试者需转录最多11段短篇文本片段：其中第一段固定为200字符，所有受试者均使用该文本；其余文本长度为40-115字符，从童话《小王子》中伪随机选取。数据通过本研究定制开发的安卓系统输入法进行采集。有关实验设计、材料与方法的详细信息可参见下文提及的相关研究论文。

数据包含原始按键按下与释放时间戳（单位：毫秒）序列，以及触发每次按键的归一化压力值（范围0.000-1.000），对应每段文本转录过程中连续敲击的按键序列。'Data'文件夹中的数据按受试者分设子文件夹，每个子文件夹包含若干.txt文件，每个文件对应一名受试者转录的一段文本片段。文件命名格式为S##_TEX##.txt，其中S##代表受试者编码ID，TEX##代表转录文本的序号。对于所有受试者，文件S##_TEX01.txt对应初始的200字符通用文本片段。

每个文件包含原始按键按下/释放时间戳（Tp#、Tr#）与归一化压力值（NP#）的序列，格式如下：
{ 按下, Tp1, 释放, Tr1, NP1 按下, Tp2, 释放, Tr2, NP2 … 按下, Tpn, 释放, Trn, NPn }
其中1、2、…、n代表打字过程中敲击按键的序列序号。

注：33名受试者中，32名成功转录了8至11段文本片段，剩余1名（受试者ID：16）仅完成5段。另有10名受试者（受试者ID：6、14、16、17、25、27、29、31、32、33）未能完整转录初始的200字符文本片段。

本数据集还包含一份微软Excel格式文件（Demographics_Clinical_Characteristics.xlsx），记录了受试者的人口统计学与临床（针对PD）特征。Excel文件中的条目通过受试者编码ID与受试者子文件夹及单个按键数据文本文件关联。

人口统计学特征包括：年龄；性别；教育水平；使用智能手机的年限；利手1。临床特征包括：分组（PD、对照）；确诊年限；Hoehn-Yahr疾病分期；帕金森病累及最严重的肢体侧2；左旋多巴等效日剂量；统一帕金森病评定量表第三部分（Unified Parkinson's Disease Rating Scale Part III, UPDRS_III）总分；UPDRS_III第21项：右侧手部震颤；UPDRS_III第21项：左侧手部震颤；UPDRS_III第22项：右侧肢体僵直；UPDRS_III第22项：左侧肢体僵直；UPDRS_III第23项：右侧手部指叩击试验；UPDRS_III第23项：左侧手部指叩击试验；UPDRS_III第31项：全身运动迟缓/运动过少。
1 利手：指用于完成精细运动技能任务的主导手。
2 帕金森病累及最严重的肢体侧。
3 UPDRS_III：统一帕金森病评定量表第三部分（运动板块）

相关研究
本数据集最初发表于以下开放获取论文中并得到详细阐述：
[1] Iakovakis, D., Hadjidimitriou, S., Charisis, V., Bostantzopoulou, S., Katsarou, Z., & Hadjileontiadis, L. J. (2018). 触摸屏打字模式分析用于检测早期帕金森病患者精细运动技能减退. 科学报告, 8(1), 7663. https://doi.org/10.1038/s41598-018-25999-0
所有使用本数据集开展研究的论文与报告均需引用上述文献以表明出处。

伦理与资助
本数据集采集相关研究已通过希腊塞萨洛尼基亚里士多德大学医学院生物伦理委员会审核（批准号：359/3.4.17）。所有受试者在参与研究前均已签署知情同意书，其中包含允许第三方访问伪匿名化数据的条款。本研究获得欧盟地平线2020研究与创新计划资助，资助协议编号为690494——i-PROGNOSIS：智能帕金森病早期检测指导新型支持性干预措施（i-prognosis.eu）。

联系方式
有关本数据集的任何问询，请联系：
Dimitrios Iakovakis先生（电气与计算机工程师，博士研究生）
信号处理与生物医学技术研究室
电气与计算机工程系
亚里士多德大学
大学校园D栋6层
希腊塞萨洛尼基，GR54124
电话：[phone]
传真：[phone]
电子邮箱：[e-mail]

许可协议
本数据集为开放获取数据集，采用知识共享署名4.0国际许可协议（https://creativecommons.org/licenses/by/4.0/）进行授权。

免责声明
本数据集按现状提供，不附带任何形式的担保。数据集管理员不对因使用本数据集导致的任何形式损害（包括人身、财产或其他损害）承担责任。