dispel.providers.generic.tasks.ps module#

Pronation Supination assessment related functionality.

This module contains functionality to extract measures for the Pronation Supination assessment (PS).

dispel.providers.generic.tasks.ps.ACTIVE_PHASE_DUR = Timedelta('0 days 00:00:07')#: Define the duration of the active test phase of the pronation supination test.

class dispel.providers.generic.tasks.ps.AggregateAmplitude[source]#

Bases: AggregateRawDataSetColumn

An aggregation processing step for the amplitude peak to peak.

aggregations: AggregationsDefinitionType = [('mean', 'mean'), ('median', 'median'), (<function npcv>, 'non parametric coefficient of variation')]#

column_id: str = 'abs_rotation'#

data_set_ids: str | Iterable[str] = 'ps_event_peak_peak'#: An iterable of data sets to be being processed

definition: ValueDefinition | ValueDefinitionPrototype | None = <dispel.data.measures.MeasureValueDefinitionPrototype object>#: The specification of the measure definition

class dispel.providers.generic.tasks.ps.AggregateAmplitudeAndDurationGroup[source]#

Bases: ProcessingStepGroup

Aggregate amplitude and duration group.

steps: List[ProcessingStep] = [<dispel.processing.level.ProcessingStepGroup object>, <dispel.processing.level.ProcessingStepGroup object>]#

class dispel.providers.generic.tasks.ps.AggregateDuration[source]#

Bases: AggregateRawDataSetColumn

An aggregation processing step for the duration peak to peak.

aggregations: AggregationsDefinitionType = [('mean', 'mean')]#

column_id: str = 'delta_t'#

data_set_ids: str | Iterable[str] = 'ps_event_peak_peak'#: An iterable of data sets to be being processed

definition: ValueDefinition | ValueDefinitionPrototype | None = <dispel.data.measures.MeasureValueDefinitionPrototype object>#: The specification of the measure definition

class dispel.providers.generic.tasks.ps.AggregateMotion[source]#

Bases: AggregateRawDataSetColumn

An Aggregation of motion measures.

__init__(data_set_id, column_id, movement, **kwargs)[source]#

Parameters:

data_set_id (str) –
column_id (str) –
movement (Movement) –

get_data_frames(level)[source]#

Get the raw data from all data sets in question.

Parameters:: level (Level) – The level from which to get the data sets.
Returns:: A list of all raw data frames with the specified ids masked with event being equal to the movement specified.
Return type:: List[pandas.DataFrame]

class dispel.providers.generic.tasks.ps.AggregatePerHandAndMotionGroup[source]#

Bases: ProcessingStepGroup

Aggregate per hand and motion group.

steps: List[ProcessingStep] = [<dispel.processing.level.ProcessingStepGroup object>, <dispel.processing.level.ProcessingStepGroup object>, <dispel.processing.level.ProcessingStepGroup object>, <dispel.processing.level.ProcessingStepGroup object>, <dispel.processing.level.ProcessingStepGroup object>, <dispel.processing.level.ProcessingStepGroup object>]#

class dispel.providers.generic.tasks.ps.BDHPronationSupinationSteps[source]#

Bases: ProcessingStepGroup

Generic Pronation Supination processing steps.

kwargs: Dict[str, Any] = {'task_name': Pronation-Supination Assessment (PS)}#

steps: List[ProcessingStep] = [<dispel.providers.generic.tasks.ps.PreprocessingPSGroup object>, <dispel.providers.generic.tasks.ps.MovementPowerGroup object>, <dispel.providers.generic.tasks.ps.EventDetectionAndFiltering object>, <dispel.providers.generic.tasks.ps.EventMeasureExtractionGroup object>]#

dispel.providers.generic.tasks.ps.COL_TO_AGG: List[str] = ['abs_rotation', 'abs_rotation_speed']#: Columns of the event data set that we want to aggregate as measures over the different events.

class dispel.providers.generic.tasks.ps.EventDetectionAndFiltering[source]#

Bases: ProcessingStepGroup

Pronation Supination event detection and filtering processing steps group.

steps: List[ProcessingStep] = [<dispel.providers.generic.sensor.Upsample object>, <dispel.providers.generic.sensor.TransformFindZeroCrossings object>, <dispel.providers.generic.tasks.ps.TransformIntegrateBetweenZeros object>, <dispel.providers.generic.tasks.ps.TransformIdentifyEvent object>, <dispel.providers.generic.tasks.ps.TransformFilterEvent object>, <dispel.providers.generic.tasks.ps.TransformRemovePriorEvent object>]#

class dispel.providers.generic.tasks.ps.EventMeasureExtractionGroup[source]#

Bases: ProcessingStepGroup

Pronation Supination event-based measure extraction group.

steps: List[ProcessingStep] = [<dispel.providers.generic.tasks.ps.TransformRotationSpeed object>, <dispel.providers.generic.tasks.ps.TransformAmplitudePeakToPeak object>, <dispel.providers.generic.tasks.ps.AggregateAmplitudeAndDurationGroup object>, <dispel.providers.generic.tasks.ps.AggregatePerHandAndMotionGroup object>, <dispel.providers.generic.tasks.ps.PerHandEventExtractionGroup object>]#

class dispel.providers.generic.tasks.ps.ExtractAmplitudeDecrementSimple[source]#

Bases: ExtractStep

Extract the simple version of decrement in amplitude.

data_set_ids: str | Iterable[str] = 'ps_event_peak_peak'#: An iterable of data sets to be being processed

static decrement_amplitude_simple(data)[source]#

Compute the simple decrement of amplitude.

Parameters:: data (DataFrame) –
Return type:: float

definition: ValueDefinition | ValueDefinitionPrototype | None = <dispel.data.measures.MeasureValueDefinitionPrototype object>#: The specification of the measure definition

description = 'The simple decrement of amplitude defined as the difference in median amplitude between the first and last 25% of the task.'#

class dispel.providers.generic.tasks.ps.ExtractAvgMovementPowerFromTimeSeries[source]#

Bases: ExtractStep

Extract average movement power from a time series.

static average_power(data)[source]#

Compute the average power of the time series.

Parameters:: data (DataFrame) –
Return type:: int

definition: ValueDefinition | ValueDefinitionPrototype | None = <dispel.data.measures.MeasureValueDefinitionPrototype object>#: The specification of the measure definition

description = 'The average power of the signal in the defined 0 - 4 Hz frequency band.'#

class dispel.providers.generic.tasks.ps.ExtractNEvent[source]#

Bases: ExtractStep

Extract number of events that are either pronation or supination.

static count_events(data)[source]#

Count the number of pronation or supination.

Parameters:: data (DataFrame) –
Return type:: int

data_set_ids: str | Iterable[str] = 'ps_event'#: An iterable of data sets to be being processed

definition: ValueDefinition | ValueDefinitionPrototype | None = <dispel.data.measures.MeasureValueDefinitionPrototype object>#: The specification of the measure definition

description = 'The number of events that are a pronation or a supination.'#

class dispel.providers.generic.tasks.ps.ExtractSpeedDecrementSimple[source]#

Bases: ExtractStep

Extract the simple version of decrement in speed.

data_set_ids: str | Iterable[str] = 'ps_event'#: An iterable of data sets to be being processed

static decrement_speed_simple(data)[source]#

Compute the simple decrement of speed.

Parameters:: data (DataFrame) –
Return type:: float

definition: ValueDefinition | ValueDefinitionPrototype | None = <dispel.data.measures.MeasureValueDefinitionPrototype object>#: The specification of the measure definition

description = 'The simple decrement of speed defined as the difference in median speed between the first and last 25% of the task.'#

dispel.providers.generic.tasks.ps.MIN_EVENT_ROTATION = 30#: Define the minimal rotation of a valid event such as pronation and supination.

class dispel.providers.generic.tasks.ps.Movement[source]#

Bases: AVEnum

Enumerated constant representing the event modalities.

PRONATION = 1#

PROSUP = 3#

SUPINATION = 2#

class dispel.providers.generic.tasks.ps.MovementPowerGroup[source]#

Bases: ProcessingStepGroup

Pronation Supination movement power processing steps group.

steps: List[ProcessingStep] = [<dispel.processing.transform.Apply object>, <dispel.providers.generic.tasks.ps.ExtractAvgMovementPowerFromTimeSeries object>]#

class dispel.providers.generic.tasks.ps.PerHandEventExtractionGroup[source]#

Bases: ProcessingStepGroup

Pronation Supination per hand measure extraction group.

steps: List[ProcessingStep] = [<dispel.processing.level.ProcessingStepGroup object>, <dispel.processing.level.ProcessingStepGroup object>]#

class dispel.providers.generic.tasks.ps.PreprocessingPSGroup[source]#

Bases: ProcessingStepGroup

Pronation Supination preprocessing steps.

steps: List[ProcessingStep] = [<dispel.providers.generic.sensor.SetTimestampIndex object>, <dispel.providers.generic.sensor.Resample object>, <dispel.processing.transform.Apply object>]#

class dispel.providers.generic.tasks.ps.TransformAmplitudePeakToPeak[source]#

Bases: TransformStep

Compute amplitude of rotation peak to peak.

static compute_abs_rot_peak_peak(data)[source]#

Compute absolute rotation peak to peak of pronation - supination.

Parameters:: data (DataFrame) –
Return type:: DataFrame

definitions: List[RawDataValueDefinition] = [<RawDataValueDefinition: start (Start timestamp indicating the beginning of the event.)>, <RawDataValueDefinition: end (end timestamp indicating the end of the event.)>, <RawDataValueDefinition: delta_t (Duration of the motion., s)>, <RawDataValueDefinition: abs_rotation (Absolute rotation for a pronation supination in degrees., deg)>]#

new_data_set_id: str = 'ps_event_peak_peak'#

class dispel.providers.generic.tasks.ps.TransformFilterEvent[source]#

Bases: TransformStep

Enrich event with time boundaries and only keep defined event.

definitions: List[RawDataValueDefinition] = [<RawDataValueDefinition: zero_crossings (zero crossings)>, <RawDataValueDefinition: rotation (rotation, deg)>, <RawDataValueDefinition: abs_rotation (absolute rotation, deg)>, <RawDataValueDefinition: event (Event indicating if the motion was a pronation or supination.)>, <RawDataValueDefinition: start (Start timestamp indicating the beginning of the event.)>, <RawDataValueDefinition: end (end timestamp indicating the end of the event.)>]#

static filter_event(ps_event)[source]#

Add start and end of event and keep only defined events.

Parameters:: ps_event (DataFrame) –
Return type:: DataFrame

new_data_set_id: str = 'ps_event'#

class dispel.providers.generic.tasks.ps.TransformIdentifyEvent[source]#

Bases: TransformStep

Identify pronation supination given the rotation and the hand used.

Only pronation event and supination event for which the associated rotation is greater than MIN_EVENT_ROTATION in absolute value are considered.

definitions: List[RawDataValueDefinition] = [<RawDataValueDefinition: zero_crossings (zero crossings)>, <RawDataValueDefinition: rotation (rotation, deg)>, <RawDataValueDefinition: abs_rotation (absolute rotation, deg)>, <RawDataValueDefinition: event (Event indicating if the motion was a pronation or supination.)>]#

static identify_event(ps_event, level)[source]#

Identify whether the event is a supination or a pronation.

Parameters:

ps_event (DataFrame) –
level (Level) –

Return type:

DataFrame

new_data_set_id: str = 'ps_event'#

class dispel.providers.generic.tasks.ps.TransformIntegrateBetweenZeros[source]#

Bases: TransformStep

Integrate gyroscope signal between zero crossings.

definitions: List[RawDataValueDefinition] = [<RawDataValueDefinition: zero_crossings (zero crossings)>, <RawDataValueDefinition: rotation (rotation, deg)>, <RawDataValueDefinition: abs_rotation (absolute rotation, deg)>]#

static integrate_between_zeros(data, zeros)[source]#

Integrate gyroscope between zero-crossings.

Parameters:

data (DataFrame) –
zeros (DataFrame) –

Return type:

DataFrame

new_data_set_id: str = 'ps_event'#

class dispel.providers.generic.tasks.ps.TransformRemovePriorEvent[source]#

Bases: TransformStep

Remove event ending before active test phase.

definitions: List[RawDataValueDefinition] = [<RawDataValueDefinition: zero_crossings (zero crossings)>, <RawDataValueDefinition: rotation (rotation, deg)>, <RawDataValueDefinition: abs_rotation (absolute rotation, deg)>, <RawDataValueDefinition: event (Event indicating if the motion was a pronation or supination.)>, <RawDataValueDefinition: start (Start timestamp indicating the beginning of the event.)>, <RawDataValueDefinition: end (end timestamp indicating the end of the event.)>]#

new_data_set_id: str = 'ps_event'#

static truncate_active_event(ps_event, level)[source]#

Remove potential event ending prior the active phase of 7 s.

Parameters:

ps_event (DataFrame) –
level (Level) –

Return type:

DataFrame

class dispel.providers.generic.tasks.ps.TransformRotationSpeed[source]#

Bases: TransformStep

Compute rotation speed per motion.

static compute_rot_speed(data)[source]#

Compute average rotation speed during a pronation or supination.

Parameters:: data (DataFrame) –
Return type:: DataFrame

definitions: List[RawDataValueDefinition] = [<RawDataValueDefinition: zero_crossings (zero crossings)>, <RawDataValueDefinition: rotation (rotation, deg)>, <RawDataValueDefinition: abs_rotation (absolute rotation, deg)>, <RawDataValueDefinition: event (Event indicating if the motion was a pronation or supination.)>, <RawDataValueDefinition: start (Start timestamp indicating the beginning of the event.)>, <RawDataValueDefinition: end (end timestamp indicating the end of the event.)>, <RawDataValueDefinition: delta_t (Duration of the motion., s)>, <RawDataValueDefinition: rotation_speed (Average rotation speed in degrees during the motion., deg)>, <RawDataValueDefinition: abs_rotation_speed (Absolute value of the average rotation speed in degrees., deg)>]#

new_data_set_id: str = 'ps_event'#

dispel.providers.generic.tasks.ps.decrement_simple(data)[source]#

Compute simplified version of decrement of a series.

Parameters:: data (Series) –
Return type:: float