| Title: | A Comprehensive Collection of Health and Human Motion Datasets |
|---|---|
| Description: | 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. Designed for researchers, analysts, and students, the package facilitates exploration and analysis of data related to health monitoring, physical activity, and rehabilitation. |
| Authors: | Oscar Alejandro Sialer Gallo [aut, cre] (ORCID: <https://orcid.org/0009-0006-0847-7374>) |
| Maintainer: | Oscar Alejandro Sialer Gallo <[email protected]> |
| License: | MIT + file LICENSE |
| Version: | 0.2.0 |
| Built: | 2026-05-27 09:15:55 UTC |
| Source: | https://github.com/alejandrosialer/healthmotionr |
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.
data(acceldata_list)data(acceldata_list)
A list with 4 components:
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.
A data frame with 1,526 observations and 3 variables:
Integer identifying the individual
Integer indicating the label of the day
Integer providing an alternative identifier of the individual
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).
A data frame containing demographic information for the 218 participants with 5 variables:
Integer identifying the participant
Integer indicating age
Factor with 2 levels indicating sex
Numeric variable with body mass index
Factor with 2 levels indicating race
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.
Data taken from the accelmissing package version 2.2.
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().
data(acceldata2_list)data(acceldata2_list)
A list with 4 components:
An integer matrix with 1,288 rows (daily profiles) and 1,440 columns (minute-by-minute accelerometer counts).
A data frame with 1,288 observations and 3 variables:
Integer identifier of the profile
Integer indicating the day label
Integer providing an alternative identifier of the individual
A numeric matrix with the same dimensions as PA, containing quality
indicators (e.g., 0 = valid, 1 = flagged).
A data frame with 184 observations and 5 variables:
Integer identifying the participant
Integer indicating age
Factor with 2 levels indicating sex
Numeric variable with body mass index
Factor with 2 levels indicating race
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.
Data taken from the accelmissing package version 2.2.
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.
data(accelimp_list)data(accelimp_list)
A list with 1 component:
A numeric matrix with 1,288 rows (daily profiles) and 1,440 columns (minute-by-minute accelerometer counts), containing the imputed accelerometer data.
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.
Data taken from the accelmissing package version 2.2.
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.
data(admiral_vs_tbl_df)data(admiral_vs_tbl_df)
A data frame with 29,643 observations and 24 variables:
Character string indicating the study identifier
Character string indicating the domain abbreviation
Character string indicating the unique subject identifier
Numeric value indicating the sequence number
Character string indicating the vital signs test short name
Character string indicating the vital signs test name
Character string indicating the subject’s position during measurement
Character string indicating the result or finding in original units
Character string indicating the original measurement units
Character string indicating the character result/finding in standard format
Numeric value indicating the result/finding in standard units
Character string indicating the standard units
Character string indicating the completion status
Character string indicating the location of the measurement
Character string indicating whether the value is a baseline flag
Numeric value indicating the visit number
Character string indicating the visit name
Numeric value indicating the planned study day of the visit
Character string indicating the date/time of measurements
Numeric value indicating the study day of vital signs
Character string indicating the planned time point name
Numeric value indicating the planned time point number
Character string indicating the planned elapsed time from the time point reference
Character string indicating the time point reference
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.
Data taken from the admiral.test package version 0.7.0.
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.
data(angle_walk_array)data(angle_walk_array)
A 3-dimensional numeric array with 1,560 values and dimensions:
Movement cycle points
Individual subjects (boys)
Joint angle type: "Hip Angle", "Knee Angle"
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.
Data taken from the fda package version 6.3.0.
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.
data(AtrialFibrillation_list)data(AtrialFibrillation_list)
A list with 2 components:
A list of 30 numeric matrices, each of dimension 640 × 2, representing two-channel ECG recordings.
A numeric vector of length 30, indicating the class labels associated with each multivariate time series.
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.
Data taken from the mlmts package, version 1.1.2.
This dataset, BasicMotions_list, is a multivariate time series (MTS) of four students performing four different activities while wearing a smart watch.
data(BasicMotions_list)data(BasicMotions_list)
A list with 2 components:
A list of 80 numeric matrices, each of dimension 100 × 6, representing six-channel sensor recordings from the smart watch.
A numeric vector of length 80, indicating the class labels associated with each multivariate time series.
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.
Data taken from the mlmts package, version 1.1.2.
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.
data(body_metrics_df)data(body_metrics_df)
A data frame with 130 observations and 3 variables:
Numeric vector indicating the body temperature of each individual (degrees Fahrenheit)
Integer code indicating the gender of the individual
Integer vector indicating the heart rate (beats per minute)
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.
Data taken from the UsingR package version 2.0-7.
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.
data(FingerMovements_char)data(FingerMovements_char)
A character vector of length 1, containing instructions for accessing the full dataset from the ueadata1 package.
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.
Data taken from the mlmts package, version 1.1.2.
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.
data(HandMovementDir_char)data(HandMovementDir_char)
A character vector of length 1, containing instructions for accessing the full dataset from the ueadata1 package.
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.
Data taken from the mlmts package, version 1.1.2.
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.
healthmotionR: A Comprehensive Collection of Health and Human Motion Datasets
A Comprehensive Collection of Health and Human Motion Datasets.
Maintainer: Oscar Alejandro Sialer Gallo [email protected]
Useful links:
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.
data(Heartbeat_char)data(Heartbeat_char)
A character vector of length 1, containing instructions for accessing the full dataset from the ueadata1 package.
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.
Data taken from the mlmts package, version 1.1.2.
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*.
data(infant_walking_df)data(infant_walking_df)
A data frame with 6 observations and 2 variables:
Numeric vector indicating the age at which infants in the exercise group began walking (months)
Numeric vector indicating the age at which infants in the no-exercise group began walking (months)
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.
Data taken from the IIS package version 1.1.
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.
data(KinData_df)data(KinData_df)
A data frame with the following variables:
numeric
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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.
Data taken from the PredPsych package version 0.4.
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.
data(knee_speed_tbl_df)data(knee_speed_tbl_df)
A tibble with 2 variables:
Numeric values indicating peak knee velocity at flexion
Numeric values indicating peak knee velocity at extension
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.
Data taken from the pubh package version 2.0.0.
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.
data(meniscal_list)data(meniscal_list)
A list with 3 numeric components, each containing 6 observations:
Numeric vector. Load at failure values for menisci repaired with the FasT-Fix system.
Numeric vector. Load at failure values for menisci repaired with biodegradable Meniscus Arrows.
Numeric vector. Load at failure values for menisci repaired with Vertical Mattress Sutures.
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.
Data taken from the IIS package, version 1.1.
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.
data(motion_sense_list)data(motion_sense_list)
A list of length 2:
Numeric matrix of dimensions 200 × 96 containing acceleration measurements for each participant across activities
Numeric matrix of dimensions 200 × 96 containing pitch angle measurements for each participant across activities
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.
Data taken from the ReMFPCA package version 2.0.0.
This dataset, motionpaths_list, is a list containing simulated motion paths. It includes trajectories represented as numeric matrices and corresponding group classifications.
data(motionpaths_list)data(motionpaths_list)
A list with 2 components:
A numeric matrix with dimensions [40, 10], representing simulated motion trajectories
A factor vector with 4 levels indicating group classifications
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.
Data taken from the RRPP package version 2.1.2.
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).
data(osteoarthritis_df)data(osteoarthritis_df)
A data frame with 2,585 observations and 7 variables:
Integer vector indicating the participant's age
Factor indicating the participant's sex (2 levels)
Numeric vector indicating the body mass index of the participant
Factor indicating the participant's race (4 levels)
Factor indicating the smoking status (2 levels)
Factor indicating osteoarthritis status at baseline (2 levels)
Factor indicating knee osteoarthritis status at follow-up (2 levels)
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.
Data taken from the MatchThem package version 1.2.1.
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.
data(rheuma_df)data(rheuma_df)
A data frame with 10 observations and 3 variables:
Factor indicating the treatment group (2 levels: new agent or active control)
Ordered factor indicating improvement on a five-point assessment scale
Integer indicating the number of patients in each category
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.
Data taken from the Fahrmeir package version 2016.5.31.
This dataset, run_biomech_tbl_df, is a tibble containing biomechanics data of human
subjects () 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.
data(run_biomech_tbl_df)data(run_biomech_tbl_df)
A tibble with 1,832 observations and 26 variables:
Numeric identifier for the subject.
Character string indicating the recording date.
Character string specifying the source filename.
Numeric value for treadmill running speed.
Numeric value for subject's age.
Numeric value for subject's height (in cm).
Numeric value for subject's weight (in kg).
Character string indicating subject's gender.
Character string indicating the dominant leg.
Character string indicating the injury definition.
Character string indicating the injured joint.
Character string indicating the injured side.
Character string specifying the injury type.
Numeric value for injury duration (in weeks).
Character string for additional injured joint information.
Character string for additional injured side information.
Character string for additional specific injury information.
Character string indicating physical activities.
Character string indicating running level.
Numeric value for years of running experience.
Character string indicating typical race distance.
Character string for race completion time (hours).
Character string for race completion time (minutes).
Character string for race completion time (seconds).
Numeric value for year of personal record.
Numeric value indicating number of races completed.
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.
Data taken from figshare: https://plus.figshare.com/articles/dataset/Running_Injury_Clinic_Kinematic_Dataset/24255795/1?file=42637039
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.
data(StandWalkJump_list)data(StandWalkJump_list)
A list with 2 components:
A list of 27 numeric matrices, each of dimension 2500 × 4, representing ECG signals recorded during different physical activities.
Numeric vector of length 27 indicating the activity label corresponding to each trial.
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.
Data taken from the mlmts package, version 1.1.2.
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.
data(Stepping_df)data(Stepping_df)
A data frame with 30 observations and 6 variables:
Numeric vector indicating the order of the measurement.
Numeric vector indicating the block or session number.
Factor with 2 levels indicating step height (1 = Low, 2 = High).
Factor with 3 levels indicating stepping frequency (1 = Slow, 2 = Medium, 3 = Fast).
Numeric vector indicating the subject's heart rate before the trial (beats per minute).
Numeric vector indicating the subject's heart rate after the trial (beats per minute).
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.
Data taken from the sur package version 1.0.4.
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.
data(surgerydat_df)data(surgerydat_df)
A data frame with 32,529 observations and 9 variables:
Numeric vector indicating the patient’s entry time into the study (in days)
Numeric vector indicating survival time (in days)
Numeric indicator of censoring status
Numeric vector identifying the hospital unit (1–45)
Numeric vector indicating the true failure rate of the hospital
Numeric vector indicating the hospital’s patient arrival rate ()
Numeric vector indicating the patient’s age (in years)
Factor with 2 levels indicating patient sex
Numeric vector indicating the patient’s body mass index
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 . Hospital-specific hazard rate
increases were sampled from a normal distribution:
This means that the average failure rate of hospitals in the dataset is the baseline
(), with some hospitals experiencing higher or lower rates. The true
failure rate is given in the variable exptheta. Patient arrival rates
() 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.
Data taken from the success package version 1.1.1.
This function lists all datasets available in the 'healthmotionR' package. If the 'healthmotionR' package is not loaded, it stops and shows an error message. If no datasets are available, it returns a message and an empty vector.
view_datasets_healthmotionR()view_datasets_healthmotionR()
A character vector with the names of the available datasets. If no datasets are found, it returns an empty character vector.
if (requireNamespace("healthmotionR", quietly = TRUE)) { library(healthmotionR) view_datasets_healthmotionR() }if (requireNamespace("healthmotionR", quietly = TRUE)) { library(healthmotionR) view_datasets_healthmotionR() }
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.
data(vs_peds_tbl_df)data(vs_peds_tbl_df)
A data frame with 164 observations and 26 variables:
Character string indicating the study identifier
Character string indicating the domain abbreviation
Character string indicating the unique subject identifier
Integer value indicating the sequence number
Character string indicating the vital signs test short name
Character string indicating the vital signs test name
Character string indicating the subject’s position during measurement
Character string indicating the result or finding in original units
Character string indicating the original measurement units
Character string indicating the character result/finding in standard format
Numeric value indicating the result/finding in standard units
Character string indicating the standard units
Character string indicating the completion status
Character string indicating the location of the measurement
Character string indicating whether the value is a baseline flag
Numeric value indicating the visit number
Character string indicating the visit name
Integer value indicating the planned study day of the visit
Character string indicating the date/time of measurements
Integer value indicating the study day of vital signs
Character string indicating the planned time point name
Numeric value indicating the planned time point number
Character string indicating the planned elapsed time from the time point reference
Character string indicating the time point reference
Character string indicating the evaluator
Character string indicating the epoch classification
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.
Data taken from the pharmaversesdtm package version 1.3.1.
This dataset, walk_biomech_tbl_df, is a tibble containing biomechanics data of human
subjects () 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.
data(walk_biomech_tbl_df)data(walk_biomech_tbl_df)
A tibble with 2,088 observations and 26 variables:
Numeric identifier for the subject.
Datetime object indicating the recording date.
Character string specifying the source filename.
Numeric value for treadmill walking speed.
Numeric value for subject's age.
Numeric value for subject's height (in cm).
Numeric value for subject's weight (in kg).
Character string indicating subject's gender.
Character string indicating the dominant leg.
Character string indicating the injury definition.
Character string indicating the injured joint.
Character string indicating the injured side.
Character string specifying the injury type.
Numeric value for injury duration (in weeks).
Character string for additional injured joint information.
Character string for additional injured side information.
Character string for additional specific injury information.
Character string indicating physical activities.
Character string indicating running level.
Numeric value for years of running experience.
Character string indicating typical race distance.
Character string for race completion time (hours).
Character string for race completion time (minutes).
Character string for race completion time (seconds).
Numeric value for year of personal record.
Numeric value indicating number of races completed.
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.
Data taken from figshare: https://plus.figshare.com/articles/dataset/Running_Injury_Clinic_Kinematic_Dataset/24255795/1?file=42637045
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.
data(walking_df) data(walking_df)data(walking_df) data(walking_df)
A data frame with 890 observations and 5 variables:
Factor indicating the sex of the participant (2 levels)
Numeric value indicating the age of the participant
Ordered factor with 4 levels related to walking activity A
Ordered factor with 4 levels related to walking activity B
Factor indicating the source of the data (3 levels)
A data frame with 29,643 observations and 24 variables:
Character string indicating the study identifier
Character string indicating the domain abbreviation
Character string indicating the unique subject identifier
Numeric value indicating the sequence number
Character string indicating the vital signs test short name
Character string indicating the vital signs test name
Character string indicating the subject’s position during measurement
Character string indicating the result or finding in original units
Character string indicating the original measurement units
Character string indicating the character result/finding in standard format
Numeric value indicating the result/finding in standard units
Character string indicating the standard units
Character string indicating the completion status
Character string indicating the location of the measurement
Character string indicating whether the value is a baseline flag
Numeric value indicating the visit number
Character string indicating the visit name
Numeric value indicating the planned study day of the visit
Character string indicating the date/time of measurements
Numeric value indicating the study day of vital signs
Character string indicating the planned time point name
Numeric value indicating the planned time point number
Character string indicating the planned elapsed time from the time point reference
Character string indicating the time point reference
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.
Data taken from the TrendLSW package version 1.0.2.
Data taken from the mice package version 3.18.0.
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.
data(z_labels_monitoring_df)data(z_labels_monitoring_df)
A data frame with 6 observations and 3 variables:
Character string indicating the recorded activity
Integer value indicating the start time of the activity
Integer value indicating the end time of the activity
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.
Data taken from the TrendLSW package version 1.0.2.