VirtualHandKinematics#

class myoverse.datatypes.VirtualHandKinematics(input_data, sampling_frequency)[source]#

Class for storing virtual hand kinematics data from MyoGestic [1].

Parameters:

  • input_data (np.ndarray) –

    The raw kinematics data for a virtual hand. The shape of the array should be (9, n_samples) or (n_chunks, 9, n_samples).

    Important

    The class will only accept 2D or 3D arrays.

    There is no way to check if you actually have it in (n_chunks, n_samples) or (n_chunks, 9, n_samples) format. Please make sure to provide the correct shape of the data.

  • sampling_frequency (float) – The sampling frequency of the kinematics data.

input_data#

The raw kinematics data for a virtual hand. The shape of the array should be (9, n_samples) or (n_chunks, 9, n_samples). The 9 typically represents the degrees of freedom: wrist flexion/extension, wrist pronation/supination, wrist deviation, and the flexion of all 5 fingers.

Type:

np.ndarray

sampling_frequency#

The sampling frequency of the kinematics data.

Type:

float

processed_data#

A dictionary where the keys are the names of filters applied to the kinematics data and the values are the processed kinematics data.

Type:

Dict[str, np.ndarray]

Examples

>>> import numpy as np
>>> from myoverse.datatypes import VirtualHandKinematics
>>>
>>> # Create sample virtual hand kinematics data (9 DOFs, 1000 samples)
>>> joint_data = np.random.randn(9, 1000)
>>>
>>> # Create a VirtualHandKinematics object with 100 Hz sampling rate
>>> kinematics = VirtualHandKinematics(joint_data, 100)
>>>
>>> # Access the raw data
>>> raw_data = kinematics.input_data
>>> print(f"Data shape: {raw_data.shape}")

References

Methods

__init__(input_data, sampling_frequency)

plot(representation[, nr_of_fingers, ...])

Plots the virtual hand kinematics data.
plot(representation, nr_of_fingers=5, visualize_wrist=True)[source]#

Plots the virtual hand kinematics data.

Parameters:

  • representation (str) – The representation to plot. The representation should be a 2D tensor with shape (9, n_samples) or a 3D tensor with shape (n_chunks, 9, n_samples).

  • nr_of_fingers (int, optional) – The number of fingers to plot. Default is 5.

  • visualize_wrist (bool, optional) – Whether to visualize wrist movements. Default is True.

Raises:

KeyError – If the representation does not exist.