All functions
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accelerometer_data
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Accelerometer sensor measurements |
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accelerometer_features()
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Extract accelerometer features |
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balance_data
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Device-Motion data from a performed balance activity |
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bandpass()
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Apply a pass-band filter to time series data |
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calculate_drift()
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Calculate the drift given x and y |
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clean_tapped_button_none()
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Remove duplicates in the given dataframe tap_data which have the buttonid parameter as 'TappedButtonNone' |
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coef_var()
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Calculate the Coefficient of Variation (coef_var) for a given sequence |
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default_kinematic_features()
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Default feature extraction functions for accelerometer and gyroscope data. |
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derivative()
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Take the derivative of a vector v |
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detrend()
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Detrend time series data |
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extract_features()
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Extract features from a column |
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fatigue()
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Calculate the fatigue given a vector x |
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filter_time()
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Select a specific time range from sensor data. |
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frequency_domain_energy()
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Returns energy for each 0.5Hz band in the frequency spectrum. |
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frequency_domain_summary()
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Returns statistical summary of the frequency spectrum |
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get_balance_features()
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Preprocess and extract interpretable features from balance activity. |
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get_ewt_spectrum()
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Get EWT spectrum |
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get_filtered_signal()
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Bandpass and sorted mean filter the given signal |
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get_heartrate()
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Preprocess and extract heart rate from smartphone video recordings. |
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get_hr_from_time_series()
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Given a processed time series find its period using autocorrelation
and then convert it to heart rate (bpm) |
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get_kinetic_tremor_features()
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Preprocess and extract interpretable features from kinetic tremor activity. |
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get_left_right_events_and_tap_intervals()
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Curate the raw tapping data to get Left and Right events,
after applying the threshold. |
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get_sampling_rate()
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Calculate the sampling rate. |
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get_spectrum()
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Get AR spectrum |
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get_tapping_features()
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Preprocess and extract interpretable features from screen tapping data. |
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get_tremor_features()
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Preprocess and extract interpretable features from resting and postural tremor activities. |
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get_walk_features()
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Preprocess and extract interpretable features from walk activity. |
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gravity_data
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Gravity sensor measurements |
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guanlab_model()
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This model was used to generate the top scoring
submission to the 2017 Parkinson's Disease Digital
Biomarker DREAM Challenge, Subchallenge 1
(https://www.synapse.org/#!Synapse:syn8717496/wiki/422884). |
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guanlab_nn_architecture()
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Neural net architecture for GuanLab's winning 2017 PDDB submission |
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guanlab_nn_weights
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Weights for the included GuanLab model |
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gyroscope_data
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Gyroscope sensor measurements |
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gyroscope_features()
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Extract gyroscope features |
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has_error()
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Check if a dataframe has an error column with at least one value |
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heartrate_data
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Sample heartrate data from a smartphone camera |
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integral()
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Take the integral of a vector v |
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intertap_summary_features()
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Get default tapping features for intertap distance |
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kinematic_sensor_argument_validator()
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Ensure the kinematic sensor arguments are well formed |
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kinetic_tremor_data
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Device-Motion data from a performed kinetic tremor activity |
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load_guanlab_model()
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Load the GuanLab model with weights. |
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map_groups()
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Map a function to a single column within tibble groups |
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mean_tkeo()
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Calculate the Mean Teager-Kaiser energy,
adapted from TKEO function in library(seewave) using f = 1, m = 1, M = 1 |
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mutate_acf()
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Construct a dataframe with ACF values |
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mutate_bandpass()
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Apply a pass-band filter to sensor data |
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mutate_derivative()
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Add a column which is the "derivative" of an existing column
to a time-series dataframe. |
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mutate_detrend()
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Detrend sensor data |
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mutate_integral()
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Add a column which is the "integral" of an existing column
to a time-series dataframe. |
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prepare_kinematic_sensor_args()
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Return arguments to be used in general feature functions |
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rest_tremor_data
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Device-Motion data from a performed resting tremor activity |
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sensor_features()
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Extract sensor features |
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tag_outlier_windows()
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Identify abnormal device rotations |
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tag_outlier_windows_()
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Get min and max gravity values for each window |
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tap_data
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Sample tapping data from the tapping activity on a smartphone |
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tap_data_summary_features()
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Get default tapping features |
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tapdrift_summary_features()
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Get default tapping features for tap drift |
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tapping_features()
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Extract tapping (screen sensor) features |
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tidy_sensor_data()
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Gather the axial columns |
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time_domain_summary()
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Returns statistical summary of the time series |
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transformation_imf_window()
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Generate a function for windowing sensor data after applying EMD |
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transformation_window()
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Generate a function for applying a window transformation to sensor data |
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walk_data
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Device-Motion data from a performed walk activity |
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window()
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Window the value vector of sensor data for each axis |
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window_signal()
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Window a signal |
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window_start_end_times()
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Compute start/end timestamps for each window |