healthmotionR: A Comprehensive Collection of Health and Human Motion Datasets

Description

This package provides a broad collection of datasets focused on health, biomechanics, and human motion. It includes clinical, physiological, and kinematic information from diverse sources, covering aspects such as surgery outcomes, vital signs, rheumatoid arthritis, osteoarthritis, accelerometry, gait analysis, motion sensing, and biomechanics experiments.

Details

healthmotionR: A Comprehensive Collection of Health and Human Motion Datasets

A Comprehensive Collection of Health and Human Motion Datasets.

Author(s)

Maintainer: Oscar Alejandro Sialer Gallo alejandro.sialer.gallo@gmail.com

See Also

Useful links:

• https://github.com/alejandrosialer/healthmotionR

Atrial Fibrillation Multivariate Time Series

Description

This dataset, AtrialFibrillation_list, is a multivariate time series (MTS) consisting of two-channel ECG recordings of atrial fibrillation. The database was created from data used in the Computers in Cardiology Challenge 2004.

Usage

data(AtrialFibrillation_list)

Format

A list with 2 components:

data

A list of 30 numeric matrices, each of dimension 640 × 2, representing two-channel ECG recordings.

classes

A numeric vector of length 30, indicating the class labels associated with each multivariate time series.

Details

The dataset name has been kept as 'AtrialFibrillation_list' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'list' indicates that the dataset is stored as a list object. The original content has not been modified in any way.

Source

Data taken from the mlmts package, version 1.1.2.

Basic Motions Multivariate Time Series

Description

This dataset, BasicMotions_list, is a multivariate time series (MTS) of four students performing four different activities while wearing a smart watch.

Usage

data(BasicMotions_list)

Format

A list with 2 components:

data

A list of 80 numeric matrices, each of dimension 100 × 6, representing six-channel sensor recordings from the smart watch.

classes

A numeric vector of length 80, indicating the class labels associated with each multivariate time series.

Details

The dataset name has been kept as 'BasicMotions_list' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'list' indicates that the dataset is stored as a list object. The original content has not been modified in any way.

Source

Data taken from the mlmts package, version 1.1.2.

Finger Movements Multivariate Time Series

Description

This dataset, FingerMovements_char, refers to multivariate time series (MTS) indicating the finger movements of a subject while typing at a computer keyboard. In this version, the dataset is represented as a character string with instructions on how to obtain the full dataset from an external package.

Usage

data(FingerMovements_char)

Format

A character vector of length 1, containing instructions for accessing the full dataset from the ueadata1 package.

Details

The dataset name has been kept as 'FingerMovements_char' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'char' indicates that the dataset is stored as a character object. The original content has not been modified in any way.

Source

Data taken from the mlmts package, version 1.1.2.

Hand Movement Direction Multivariate Time Series

Description

This dataset, HandMovementDir_char, refers to multivariate time series (MTS) indicating the movement of a joystick by two subjects with their hand and wrist. In this version, the dataset is represented as a character string with instructions on how to obtain the full dataset from an external package.

Usage

data(HandMovementDir_char)

Format

A character vector of length 1, containing instructions for accessing the full dataset from the ueadata1 package.

Details

The dataset name has been kept as 'HandMovementDir_char' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'char' indicates that the dataset is stored as a character object. The original content has not been modified in any way.

Source

Data taken from the mlmts package, version 1.1.2.

Heartbeat Multivariate Time Series

Description

This dataset, Heartbeat_char, refers to multivariate time series (MTS) indicating heart sound from healthy patients and pathological patients (with a confirmed cardiac diagnosis). In this version, the dataset is represented as a character string with instructions on how to obtain the full dataset from an external package.

Usage

data(Heartbeat_char)

Format

A character vector of length 1, containing instructions for accessing the full dataset from the ueadata1 package.

Details

The dataset name has been kept as 'Heartbeat_char' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'char' indicates that the dataset is stored as a character object. The original content has not been modified in any way.

Source

Data taken from the mlmts package, version 1.1.2.

KinData – Kinematics Dataset

Description

This dataset, KinData_df, is a data frame containing part of the motion capture dataset freely available in the publication by Ansuini et al. (2015). It provides detailed kinematic measurements of grasping movements across multiple conditions.

Usage

data(KinData_df)

Format

A data frame with the following variables:

Grip_Aperture_01

numeric

Grip_Aperture_02

numeric

Grip_Aperture_03

numeric

Grip_Aperture_04

numeric

Grip_Aperture_05

numeric

Grip_Aperture_06

numeric

Grip_Aperture_07

numeric

Grip_Aperture_08

numeric

Grip_Aperture_09

numeric

Grip_Aperture_10

numeric

Object.Size

numeric

Wrist_Height_01

numeric

Wrist_Height_02

numeric

Wrist_Height_03

numeric

Wrist_Height_04

numeric

Wrist_Height_05

numeric

Wrist_Height_06

numeric

Wrist_Height_07

numeric

Wrist_Height_08

numeric

Wrist_Height_09

numeric

Wrist_Height_10

numeric

Wrist_Velocity_01

numeric

Wrist_Velocity_02

numeric

Wrist_Velocity_03

numeric

Wrist_Velocity_04

numeric

Wrist_Velocity_05

numeric

Wrist_Velocity_06

numeric

Wrist_Velocity_07

numeric

Wrist_Velocity_08

numeric

Wrist_Velocity_09

numeric

Wrist_Velocity_10

numeric

x_finger_plane_01

numeric

x_finger_plane_02

numeric

x_finger_plane_03

numeric

x_finger_plane_04

numeric

x_finger_plane_05

numeric

x_finger_plane_06

numeric

x_finger_plane_07

numeric

x_finger_plane_08

numeric

x_finger_plane_09

numeric

x_finger_plane_10

numeric

x_index_01

numeric

x_index_02

numeric

x_index_03

numeric

x_index_04

numeric

x_index_05

numeric

x_index_06

numeric

x_index_07

numeric

x_index_08

numeric

x_index_09

numeric

x_index_10

numeric

x_thumb_01

numeric

x_thumb_02

numeric

x_thumb_03

numeric

x_thumb_04

numeric

x_thumb_05

numeric

x_thumb_06

numeric

x_thumb_07

numeric

x_thumb_08

numeric

x_thumb_09

numeric

x_thumb_10

numeric

y_finger_plane_01

numeric

y_finger_plane_02

numeric

y_finger_plane_03

numeric

y_finger_plane_04

numeric

y_finger_plane_05

numeric

y_finger_plane_06

numeric

y_finger_plane_07

numeric

y_finger_plane_08

numeric

y_finger_plane_09

numeric

y_finger_plane_10

numeric

y_index_01

numeric

y_index_02

numeric

y_index_03

numeric

y_index_04

numeric

y_index_05

numeric

y_index_06

numeric

y_index_07

numeric

y_index_08

numeric

y_index_09

numeric

y_index_10

numeric

y_thumb_01

numeric

y_thumb_02

numeric

y_thumb_03

numeric

y_thumb_04

numeric

y_thumb_05

numeric

y_thumb_06

numeric

y_thumb_07

numeric

y_thumb_08

numeric

y_thumb_09

numeric

y_thumb_10

numeric

z_finger_plane_01

numeric

z_finger_plane_02

numeric

z_finger_plane_03

numeric

z_finger_plane_04

numeric

z_finger_plane_05

numeric

z_finger_plane_06

numeric

z_finger_plane_07

numeric

z_finger_plane_08

numeric

z_finger_plane_09

numeric

z_finger_plane_10

numeric

z_index_01

numeric

z_index_02

numeric

z_index_03

numeric

z_index_04

numeric

z_index_05

numeric

z_index_06

numeric

z_index_07

numeric

z_index_08

numeric

z_index_09

numeric

z_index_10

numeric

z_thumb_01

numeric

z_thumb_02

numeric

z_thumb_03

numeric

z_thumb_04

numeric

z_thumb_05

numeric

z_thumb_06

numeric

z_thumb_07

numeric

z_thumb_08

numeric

z_thumb_09

numeric

z_thumb_10

numeric

Details

The dataset includes information on wrist velocity, grip aperture, wrist height, and three-dimensional coordinates of the index finger, thumb, and finger plane. Each measurement is recorded across 10 equally spaced points of the movement trajectory. The variable Object.Size indicates the size of the object being grasped.

The dataset name has been kept as KinData_df to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix _df indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the PredPsych package version 0.4.

StandWalkJump Multivariate Time Series

Description

This dataset, StandWalkJump_list, is a multivariate time series (MTS) involving short-duration ECG signals recorded from a healthy 25-year-old male performing different physical activities. The dataset is structured to allow analysis of physiological responses across 27 separate trials.

Usage

data(StandWalkJump_list)

Format

A list with 2 components:

data

A list of 27 numeric matrices, each of dimension 2500 × 4, representing ECG signals recorded during different physical activities.

classes

Numeric vector of length 27 indicating the activity label corresponding to each trial.

Details

The dataset name has been kept as 'StandWalkJump_list' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'list' indicates that the dataset is a list structure. The original content has not been modified in any way.

Source

Data taken from the mlmts package, version 1.1.2.

Stepping and Heart Rate

Description

This dataset, Stepping_df, is a data frame containing heart rate measurements of subjects performing stepping exercises at different heights and frequencies. Each subject's resting heart rate was measured before a trial (HRInit) and after stepping (HRFinal). Step heights include 5.75 inches (Low) and 11.5 inches (High), and stepping frequencies include 14 steps/min (Slow), 21 steps/min (Medium), and 28 steps/min (Fast), resulting in six possible height/frequency combinations. Each trial lasted three minutes, with subjects kept on pace by an electric metronome and heart rate counted by an experimenter.

Usage

data(Stepping_df)

Format

A data frame with 30 observations and 6 variables:

Order

Numeric vector indicating the order of the measurement.

Block

Numeric vector indicating the block or session number.

Height

Factor with 2 levels indicating step height (1 = Low, 2 = High).

Freq

Factor with 3 levels indicating stepping frequency (1 = Slow, 2 = Medium, 3 = Fast).

HRInit

Numeric vector indicating the subject's heart rate before the trial (beats per minute).

HRFinal

Numeric vector indicating the subject's heart rate after the trial (beats per minute).

Details

The dataset name has been kept as 'Stepping_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the sur package version 1.0.4.

Accelerometer Data Example 2

Description

Data example from the 2003-2004 National Health and Nutrition Examination Survey (NHANES) dataset. This example includes 184 individuals, giving 1,288 daily profiles. It only includes valid subjects with at least three complete days, obtained as a subset of acceldata_list using the function valid.subjects().

Usage

data(acceldata2_list)

Format

A list with 4 components:

PA

An integer matrix with 1,288 rows (daily profiles) and 1,440 columns (minute-by-minute accelerometer counts).

label

A data frame with 1,288 observations and 3 variables:

id

Integer identifier of the profile

day

Integer indicating the day label

personid2

Integer providing an alternative identifier of the individual

flag

A numeric matrix with the same dimensions as PA, containing quality indicators (e.g., 0 = valid, 1 = flagged).

demo

A data frame with 184 observations and 5 variables:

personid

Integer identifying the participant

age

Integer indicating age

sex

Factor with 2 levels indicating sex

bmi

Numeric variable with body mass index

race

Factor with 2 levels indicating race

Details

The dataset name has been kept as 'acceldata2_list' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'list' indicates that the dataset is stored as a list containing multiple components. The original content has not been modified in any way.

Source

Data taken from the accelmissing package version 2.2.

Accelerometer Data Example

Description

Data example from the 2003-2004 National Health and Nutrition Examination Survey (NHANES) dataset. This example only includes 218 individuals, which gives 1,526 daily profiles, from a total of 7,176 participants in the physical activity survey.

Usage

data(acceldata_list)

Format

A list with 4 components:

PA

A data frame with 1,526 observations and 1,440 variables. Each row corresponds to a daily profile, with columns V1 to V1440 representing accelerometer counts recorded minute by minute throughout the day.

label

A data frame with 1,526 observations and 3 variables:

personid

Integer identifying the individual

daylabel

Integer indicating the label of the day

personid2

Integer providing an alternative identifier of the individual

flag

A data frame with 1,526 observations and 1,440 variables. The structure mirrors that of PA, with values indicating data quality (e.g., 0 = valid, 1 = flagged).

demo

A data frame containing demographic information for the 218 participants with 5 variables:

personid

Integer identifying the participant

age

Integer indicating age

sex

Factor with 2 levels indicating sex

bmi

Numeric variable with body mass index

race

Factor with 2 levels indicating race

Details

The dataset name has been kept as 'acceldata_list' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'list' indicates that the dataset is stored as a list containing multiple data frames. The original content has not been modified in any way.

Source

Data taken from the accelmissing package version 2.2.

Accelerometer Data Example with Imputations

Description

This dataset, accelimp_list, is a list containing imputed accelerometer data from the 2003-2004 National Health and Nutrition Examination Survey (NHANES). It includes 184 individuals, resulting in 1,288 daily profiles obtained after applying accel.impute() to the raw accelerometer data.

Usage

data(accelimp_list)

Format

A list with 1 component:

imp1

A numeric matrix with 1,288 rows (daily profiles) and 1,440 columns (minute-by-minute accelerometer counts), containing the imputed accelerometer data.

Details

The dataset name has been kept as 'accelimp_list' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'list' indicates that the dataset is stored as a list. The original content has not been modified in any way.

Source

Data taken from the accelmissing package version 2.2.

Vital Signs Dataset

Description

This dataset, admiral_vs_tbl_df, is a tibble data frame containing a CDISC SDTM VS dataset from the CDISC pilot project. It includes study identifiers, subject identifiers, vital signs test codes, test names, measurement results, visit information, and related metadata. The dataset follows the structure of clinical trial data and provides standardized vital signs information.

Usage

data(admiral_vs_tbl_df)

Format

A data frame with 29,643 observations and 24 variables:

STUDYID

Character string indicating the study identifier

DOMAIN

Character string indicating the domain abbreviation

USUBJID

Character string indicating the unique subject identifier

VSSEQ

Numeric value indicating the sequence number

VSTESTCD

Character string indicating the vital signs test short name

VSTEST

Character string indicating the vital signs test name

VSPOS

Character string indicating the subject’s position during measurement

VSORRES

Character string indicating the result or finding in original units

VSORRESU

Character string indicating the original measurement units

VSSTRESC

Character string indicating the character result/finding in standard format

VSSTRESN

Numeric value indicating the result/finding in standard units

VSSTRESU

Character string indicating the standard units

VSSTAT

Character string indicating the completion status

VSLOC

Character string indicating the location of the measurement

VSBLFL

Character string indicating whether the value is a baseline flag

VISITNUM

Numeric value indicating the visit number

VISIT

Character string indicating the visit name

VISITDY

Numeric value indicating the planned study day of the visit

VSDTC

Character string indicating the date/time of measurements

VSDY

Numeric value indicating the study day of vital signs

VSTPT

Character string indicating the planned time point name

VSTPTNUM

Numeric value indicating the planned time point number

VSELTM

Character string indicating the planned elapsed time from the time point reference

VSTPTREF

Character string indicating the time point reference

Details

The dataset name has been kept as 'admiral_vs_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the admiral.test package version 0.7.0.

Hip and Knee Angle while Walking

Description

This dataset, angle_walk_array, is a 3-dimensional array containing hip and knee angle data (in degrees) for 39 boys measured during walking. Each observation records the hip and knee joint angles across 20 equally spaced points of a movement cycle.

Usage

data(angle_walk_array)

Format

A 3-dimensional numeric array with 1,560 values and dimensions:

[1:20]

Movement cycle points

[1:39]

Individual subjects (boys)

[1:2]

Joint angle type: "Hip Angle", "Knee Angle"

Details

The dataset name has been kept as angle_walk_array to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix _array indicates that the dataset is an array. The original content has not been modified in any way.

Source

Data taken from the fda package version 6.3.0.

Body Temperature and Heart Rate

Description

This dataset, body_metrics_df, is a data frame containing measurements of body temperature and heart rate for 130 healthy individuals. It was used to investigate the claim that "normal" human body temperature is 98.6 degrees Fahrenheit.

Usage

data(body_metrics_df)

Format

A data frame with 130 observations and 3 variables:

temperature

Numeric vector indicating the body temperature of each individual (degrees Fahrenheit)

gender

Integer code indicating the gender of the individual

hr

Integer vector indicating the heart rate (beats per minute)

Details

The dataset name has been kept as 'body_metrics_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the UsingR package version 2.0-7.

Infant Walking

Description

This dataset, infant_walking_df, is a data frame containing the ages (in months) at which 12 infants were reported by their mothers to have started walking. The infants were randomly assigned to either an "exercise" or "no-exercise" group as part of the study conducted by Zelazo et al. (1972). The data are also presented in Table 9.8 of Wolfe and Schneider, *Intuitive Introductory Statistics*.

Usage

data(infant_walking_df)

Format

A data frame with 6 observations and 2 variables:

exercise

Numeric vector indicating the age at which infants in the exercise group began walking (months)

no_exercise

Numeric vector indicating the age at which infants in the no-exercise group began walking (months)

Details

The dataset name has been kept as 'infant_walking_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the IIS package version 1.1.

Peak Knee Velocity in Walking

Description

This dataset, knee_speed_tbl_df, is a tibble containing measurements of peak knee velocity during walking at both flexion and extension. The data originate from studies investigating functional performance in individuals with cerebral palsy.

Usage

data(knee_speed_tbl_df)

Format

A tibble with 2 variables:

flexion

Numeric values indicating peak knee velocity at flexion

extension

Numeric values indicating peak knee velocity at extension

Details

The dataset name has been kept as 'knee_speed_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is stored as a tibble (a modern data frame). The original content has not been modified in any way.

Source

Data taken from the pubh package version 2.0.0.

Meniscal Repairs Load at Failure

Description

This dataset, meniscal_list, contains the load at failure for 18 cadaveric menisci repaired by one of three techniques: the FasT-Fix Meniscal Repair Suture System (FasT-Fix), the use of biodegradable Meniscus Arrows (MA), and the Vertical Mattress Sutures (VMS) approach. The data are also presented in Table 12.1 of Wolfe and Schneider - Intuitive Introductory Statistics.

Usage

data(meniscal_list)

Format

A list with 3 numeric components, each containing 6 observations:

FasT-Fix

Numeric vector. Load at failure values for menisci repaired with the FasT-Fix system.

Meniscus Arrows

Numeric vector. Load at failure values for menisci repaired with biodegradable Meniscus Arrows.

Vertical Mattress

Numeric vector. Load at failure values for menisci repaired with Vertical Mattress Sutures.

Details

The dataset name has been kept as 'meniscal_list' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'list' indicates that the dataset is stored as a list structure. The original content has not been modified in any way.

Source

Data taken from the IIS package, version 1.1.

Motion Sense Dataset

Description

This dataset, motion_sense_list, is a list containing smartphone sensor measurements of user acceleration and pitch attitude collected from 24 individuals performing various physical activities. The dataset includes time-series data recorded by accelerometer and gyroscope sensors under consistent environmental conditions.

Usage

data(motion_sense_list)

Format

A list of length 2:

user_acceleration

Numeric matrix of dimensions 200 × 96 containing acceleration measurements for each participant across activities

pitch_attitude

Numeric matrix of dimensions 200 × 96 containing pitch angle measurements for each participant across activities

Details

Participants (n = 24) of varying gender, age, weight, and height performed four distinct activities: jogging, walking, sitting, and standing. Additional recordings also included stair movements (upstairs and downstairs).

The dataset name has been kept as 'motion_sense_list' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'list' indicates that the dataset is stored as a list object. The original content has not been modified in any way.

Source

Data taken from the ReMFPCA package version 2.0.0.

Simulated Motion Paths

Description

This dataset, motionpaths_list, is a list containing simulated motion paths. It includes trajectories represented as numeric matrices and corresponding group classifications.

Usage

data(motionpaths_list)

Format

A list with 2 components:

trajectories

A numeric matrix with dimensions [40, 10], representing simulated motion trajectories

groups

A factor vector with 4 levels indicating group classifications

Details

The dataset name has been kept as 'motionpaths_list' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'list' indicates that the dataset is a list object. The original content has not been modified in any way.

Source

Data taken from the RRPP package version 2.1.2.

Data of 2,585 Participants in the Osteoarthritis Initiative (OAI) Project

Description

This dataset, osteoarthritis_df, is a data frame containing demographic and clinical information of 2,585 individuals with or at risk of knee osteoarthritis. The dataset includes variables such as age, sex, body mass index (BMI), race, smoking status, and osteoarthritis-related outcomes. Some variables contain missing values, including BMI (quantitative), race (categorical), smoking status (binary), and knee osteoarthritis status at follow-up (binary).

Usage

data(osteoarthritis_df)

Format

A data frame with 2,585 observations and 7 variables:

AGE

Integer vector indicating the participant's age

SEX

Factor indicating the participant's sex (2 levels)

BMI

Numeric vector indicating the body mass index of the participant

RAC

Factor indicating the participant's race (4 levels)

SMK

Factor indicating the smoking status (2 levels)

OSP

Factor indicating osteoarthritis status at baseline (2 levels)

KOA

Factor indicating knee osteoarthritis status at follow-up (2 levels)

Details

The dataset name has been kept as 'osteoarthritis_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the MatchThem package version 1.2.1.

Data from Patients with Acute Rheumatoid Arthritis

Description

This dataset, rheuma_df, is a data frame containing data from patients with acute rheumatoid arthritis. A new agent was compared with an active control, and each patient was evaluated on a five-point assessment scale of improvement.

Usage

data(rheuma_df)

Format

A data frame with 10 observations and 3 variables:

Drug

Factor indicating the treatment group (2 levels: new agent or active control)

Improvement

Ordered factor indicating improvement on a five-point assessment scale

n

Integer indicating the number of patients in each category

Details

The dataset name has been kept as 'rheuma_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the Fahrmeir package version 2016.5.31.

Running Injury Clinic Kinematic Dataset

Description

This dataset, run_biomech_tbl_df, is a tibble containing biomechanics data of human subjects (N = 1,832) running on a treadmill. Data include 3D marker positions over trials ranging from 25 to 60 seconds. In addition, demographic information and calculated variables of interest (such as step width, stride rate, peak knee flexion angle) are provided. The dataset also comes with sample processing code and data analysis tutorials.

Usage

data(run_biomech_tbl_df)

Format

A tibble with 1,832 observations and 26 variables:

sub_id

Numeric identifier for the subject.

datestring

Character string indicating the recording date.

filename

Character string specifying the source filename.

speed_r

Numeric value for treadmill running speed.

age

Numeric value for subject's age.

Height

Numeric value for subject's height (in cm).

Weight

Numeric value for subject's weight (in kg).

Gender

Character string indicating subject's gender.

DominantLeg

Character string indicating the dominant leg.

InjDefn

Character string indicating the injury definition.

InjJoint

Character string indicating the injured joint.

InjSide

Character string indicating the injured side.

SpecInjury

Character string specifying the injury type.

InjDuration

Numeric value for injury duration (in weeks).

InjJoint2

Character string for additional injured joint information.

InjSide2

Character string for additional injured side information.

SpecInjury2

Character string for additional specific injury information.

Activities

Character string indicating physical activities.

Level

Character string indicating running level.

YrsRunning

Numeric value for years of running experience.

RaceDistance

Character string indicating typical race distance.

RaceTimeHrs

Character string for race completion time (hours).

RaceTimeMins

Character string for race completion time (minutes).

RaceTimeSecs

Character string for race completion time (seconds).

YrPR

Numeric value for year of personal record.

NumRaces

Numeric value indicating number of races completed.

Details

The dataset name has been kept as 'run_biomech_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is stored as a tibble (data frame). The original content has not been modified in any way.

Source

Data taken from figshare: https://plus.figshare.com/articles/dataset/Running_Injury_Clinic_Kinematic_Dataset/24255795/1?file=42637039

Simulated Surgery Procedures Data

Description

This dataset, surgerydat_df, is a data frame containing simulated data of surgery procedures performed at multiple hospitals. It includes information on patients, their survival times, and hospital-specific risk characteristics.

Usage

data(surgerydat_df)

Format

A data frame with 32,529 observations and 9 variables:

entrytime

Numeric vector indicating the patient’s entry time into the study (in days)

survtime

Numeric vector indicating survival time (in days)

censorid

Numeric indicator of censoring status

unit

Numeric vector identifying the hospital unit (1–45)

exptheta

Numeric vector indicating the true failure rate of the hospital

psival

Numeric vector indicating the hospital’s patient arrival rate (\psi)

age

Numeric vector indicating the patient’s age (in years)

sex

Factor with 2 levels indicating patient sex

BMI

Numeric vector indicating the patient’s body mass index

Details

The dataset comprises data from 45 simulated hospitals with patient arrivals occurring within the first 400 days after the start of the study. Patient survival times were determined using a risk-adjusted Cox proportional hazards model with coefficients: age = 0.003, BMI = 0.02, and sexmale = 0.2, along with an exponential baseline hazard rate h_0(t, \lambda = 0.01) e^\mu. Hospital-specific hazard rate increases were sampled from a normal distribution:

\theta \sim N(\log(1), sd = 0.4)

This means that the average failure rate of hospitals in the dataset is the baseline (\theta = 0), with some hospitals experiencing higher or lower rates. The true failure rate is given in the variable exptheta. Patient arrival rates (\psi) differ across hospitals:

• Hospitals 1–5 & 16–20: 0.5 patients per day (small hospitals)

• Hospitals 6–10 & 21–25: 1 patient per day (medium hospitals)

• Hospitals 11–15 & 26–30: 1.5 patients per day (large hospitals)

The dataset name has been kept as 'surgerydat_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the success package version 1.1.1.

Vital Signs Dataset - Pediatrics

Description

This dataset, vs_peds_tbl_df, is a tibble data frame containing an updated SDTM VS dataset with anthropometric measurements for pediatric patients. It includes study identifiers, subject identifiers, vital signs test codes, test names, measurement results, visit information, evaluator details, and epoch classification. The dataset follows the CDISC SDTM structure and is tailored for pediatric populations.

Usage

data(vs_peds_tbl_df)

Format

A data frame with 164 observations and 26 variables:

STUDYID

Character string indicating the study identifier

DOMAIN

Character string indicating the domain abbreviation

USUBJID

Character string indicating the unique subject identifier

VSSEQ

Integer value indicating the sequence number

VSTESTCD

Character string indicating the vital signs test short name

VSTEST

Character string indicating the vital signs test name

VSPOS

Character string indicating the subject’s position during measurement

VSORRES

Character string indicating the result or finding in original units

VSORRESU

Character string indicating the original measurement units

VSSTRESC

Character string indicating the character result/finding in standard format

VSSTRESN

Numeric value indicating the result/finding in standard units

VSSTRESU

Character string indicating the standard units

VSSTAT

Character string indicating the completion status

VSLOC

Character string indicating the location of the measurement

VSBLFL

Character string indicating whether the value is a baseline flag

VISITNUM

Numeric value indicating the visit number

VISIT

Character string indicating the visit name

VISITDY

Integer value indicating the planned study day of the visit

VSDTC

Character string indicating the date/time of measurements

VSDY

Integer value indicating the study day of vital signs

VSTPT

Character string indicating the planned time point name

VSTPTNUM

Numeric value indicating the planned time point number

VSELTM

Character string indicating the planned elapsed time from the time point reference

VSTPTREF

Character string indicating the time point reference

VSEVAL

Character string indicating the evaluator

EPOCH

Character string indicating the epoch classification

Details

The dataset name has been kept as 'vs_peds_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the pharmaversesdtm package version 1.3.1.

Running Injury Clinic Kinematic Dataset (Walking)

Description

This dataset, walk_biomech_tbl_df, is a tibble containing biomechanics data of human subjects (N = 2,088) walking on a treadmill. Data include 3D marker positions over trials ranging from 25 to 60 seconds. In addition, demographic information and calculated variables of interest (such as step width, stride rate, peak knee flexion angle) are provided. The dataset also comes with sample processing code and data analysis tutorials.

Usage

data(walk_biomech_tbl_df)

Format

A tibble with 2,088 observations and 26 variables:

sub_id

Numeric identifier for the subject.

datestring

Datetime object indicating the recording date.

filename

Character string specifying the source filename.

speed_w

Numeric value for treadmill walking speed.

age

Numeric value for subject's age.

Height

Numeric value for subject's height (in cm).

Weight

Numeric value for subject's weight (in kg).

Gender

Character string indicating subject's gender.

DominantLeg

Character string indicating the dominant leg.

InjDefn

Character string indicating the injury definition.

InjJoint

Character string indicating the injured joint.

InjSide

Character string indicating the injured side.

SpecInjury

Character string specifying the injury type.

InjDuration

Numeric value for injury duration (in weeks).

InjJoint2

Character string for additional injured joint information.

InjSide2

Character string for additional injured side information.

SpecInjury2

Character string for additional specific injury information.

Activities

Character string indicating physical activities.

Level

Character string indicating running level.

YrsRunning

Numeric value for years of running experience.

RaceDistance

Character string indicating typical race distance.

RaceTimeHrs

Character string for race completion time (hours).

RaceTimeMins

Character string for race completion time (minutes).

RaceTimeSecs

Character string for race completion time (seconds).

YrPR

Numeric value for year of personal record.

NumRaces

Numeric value indicating number of races completed.

Details

The dataset name has been kept as 'walk_biomech_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is stored as a tibble (data frame). The original content has not been modified in any way.

Source

Data taken from figshare: https://plus.figshare.com/articles/dataset/Running_Injury_Clinic_Kinematic_Dataset/24255795/1?file=42637045

Walking Data

Description

This dataset, walking_df, is a data frame containing demographic and categorical information from walking activity observations. It includes sex, age, ordered factors related to the walking activity, and the source of the data.

This dataset, walking_df, is a data frame containing measurements of walking disability collected in studies A, B, and E. It follows a clinical trial data structure and includes identifiers, visit information, test codes, test names, measurement results, and related metadata.

Usage

data(walking_df)

data(walking_df)

Format

A data frame with 890 observations and 5 variables:

sex

Factor indicating the sex of the participant (2 levels)

age

Numeric value indicating the age of the participant

YA

Ordered factor with 4 levels related to walking activity A

YB

Ordered factor with 4 levels related to walking activity B

src

Factor indicating the source of the data (3 levels)

A data frame with 29,643 observations and 24 variables:

STUDYID

Character string indicating the study identifier

DOMAIN

Character string indicating the domain abbreviation

USUBJID

Character string indicating the unique subject identifier

VSSEQ

Numeric value indicating the sequence number

VSTESTCD

Character string indicating the vital signs test short name

VSTEST

Character string indicating the vital signs test name

VSPOS

Character string indicating the subject’s position during measurement

VSORRES

Character string indicating the result or finding in original units

VSORRESU

Character string indicating the original measurement units

VSSTRESC

Character string indicating the character result/finding in standard format

VSSTRESN

Numeric value indicating the result/finding in standard units

VSSTRESU

Character string indicating the standard units

VSSTAT

Character string indicating the completion status

VSLOC

Character string indicating the location of the measurement

VSBLFL

Character string indicating whether the value is a baseline flag

VISITNUM

Numeric value indicating the visit number

VISIT

Character string indicating the visit name

VISITDY

Numeric value indicating the planned study day of the visit

VSDTC

Character string indicating the date/time of measurements

VSDY

Numeric value indicating the study day of vital signs

VSTPT

Character string indicating the planned time point name

VSTPTNUM

Numeric value indicating the planned time point number

VSELTM

Character string indicating the planned elapsed time from the time point reference

VSTPTREF

Character string indicating the time point reference

Details

The dataset name has been kept as 'walking_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.

The dataset name has been kept as 'walking_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the TrendLSW package version 1.0.2.

Data taken from the mice package version 3.18.0.

Activity Labels for Human Activity Monitoring

Description

This dataset, z_labels_monitoring_df, is a data frame containing the labelled activities recorded during the observation period corresponding to the data object z.acc.

Usage

data(z_labels_monitoring_df)

Format

A data frame with 6 observations and 3 variables:

activity

Character string indicating the recorded activity

start

Integer value indicating the start time of the activity

end

Integer value indicating the end time of the activity

Details

The dataset name has been kept as 'z_labels_monitoring_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the healthmotionR package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the TrendLSW package version 1.0.2.