Analyses (.ana)#

Contains functions to analyse isometric tests, Wingate tests, Sprint tests, and Submax tests on the wheelchair ergometer.

worklab.ana.ana_sprint(data, data_pbp, half=5, title=None)[source]#

Sprint test analyse. Plot a figure with the power, speed and distance for left and right separate. Also saves important outcomes

Parameters

  • data (dict) – processed and cutted ergometer data dictionary with dataframes

  • data_pbp (dict) – processed and cutted push_by_push ergometer data dictionary with dataframes

  • half (float, optional) – half-time of the sprint, default is 5 s

  • title (str, optional) – title of figure

Returns

  • fig (matplotlib.figure.Figure)

  • outcomes (dataframe)

worklab.ana.ana_submax(data_ergo, data_pbp, data_spiro)[source]#

Sub maximal test analyse. Saves important outcomes

Parameters

  • data_ergo (pd.DataFrame) – processed and cutted ergometer data

  • data_pbp (pd.DataFrame) – processed and cutted ergometer data

  • data_spiro (pd.DataFrame) – processed and cutted spirometer data

Returns

outcomes

Return type

pd.DataFrame

worklab.ana.cut_data(data, start, end, distance=True)[source]#

Cuts data to time of interest

Parameters

  • data (dict) – processed ergometer data dictionary with dataframes

  • start (float) – start time [s]

  • end (float) – end time [s]

  • distance (bool, optional) – resets distance to 0 at start, default is True.

Returns

data – data cutted to time of interest

Return type

dict

worklab.ana.isometricforce(data, title=None, height=40, distance=500, ylim=None)[source]#

Calculates the three seconds maximal user force and plots it against time (darkblue). Peaks are annotated with a dot and with the height of the peak, max value is shown in the corner. Possibility to scale manually

Parameters

  • data (dict) – processed ergometer data dictionary with dataframes

  • title (str, optional) – plotted on top of graph, default is None

  • height (float, optional) – minimal height of peak, default is 40 N

  • distance (float, optional) – minimal distance between peaks, default is 500 samples

  • ylim (list [min, max] of floats or int, optional) – list of the minimal and maximal ylim for user force in N

Returns

  • fig (matplotlib.figure.Figure)

  • peaks (series) – peaks of maximal user force (averaged over left and right)

worklab.ana.maximal1min(data, dur, title=None)[source]#

Maximal exercise test analyse. Gives a plot with the power (green) and velocity (red) for each step, also prints the important performance indicators per step:

Work [J] Mean power [W] Maximal power [W] Mean velocity [ms]

Parameters

  • data (dict) – processed and cutted ergometer data dictionary with dataframes

  • dur (int) – duration of max test in seconds

  • title (str, optional) – title of figure

Returns

  • fig (matplotlib.figure.Figure)

  • outcomes (dataframe)

worklab.ana.mean_data(data)[source]#

Combined data of left and right module Time, speed, aspeed, acc and dist are averaged Force, torque, power, work and uforce are averaged and multiplied with two

Parameters

data (dict) – processed ergometer data dictionary with dataframes for left and right

Returns

data – with left, right and mean module

Return type

dict

worklab.ana.protocol_max(p30, muser, mwc, v=1.39)[source]#

Calculates the protocol for the Maximal exercise test on a wheelchair ergometer, based on the regression equations between the isometric force, anaerobic and aerobic power.

(Janssen T.W.J., Van Oers C.A.J.M., Hollander A.P., Veeger H.E.J., Van der Woude L.H.V. Isometric strength sprint power and anaerobic power in individuals with a spinal cord injury. Med Sci Sports Exercise 1993;25(7):863-870. doi:10.1249/00005768-199307000-00016)

Parameters

  • p30 (float) – average power over a 30-sec Wingate test

  • muser (float/int) – mass user

  • mwc (float/int) – mass wheelchair

  • v (float, optional) – constant comfortable velocity for the test, default is 1.39 m/s

Return type

Print the p30, the popeak, the aimed mean velocity and the resistance for each step.

worklab.ana.protocol_wingate(fiso, muser, mwc, v=2)[source]#

Calculates the protocol for the Wingate test on a wheelchair ergometer, based on the regression equations between the isometric force, anaerobic and aerobic power.

(Janssen T.W.J., Van Oers C.A.J.M., Hollander A.P., Veeger H.E.J., Van der Woude L.H.V. Isometric strength sprint power and anaerobic power in individuals with a spinal cord injury. Med Sci Sports Exercise 1993;25(7):863-870. doi:10.1249/00005768-199307000-00016)

Parameters

  • fiso (float) – maximal 3 seconds force in N, average of left and right

  • muser (float/int) – mass user

  • mwc (float/int) – mass wheelchair

  • v (float/int, optional) – mean velocity wingate, default is 2 m/s

Returns

  • Print the maximal three seconds force, the predicted p30, the aimed mean velocity

  • and the calculated resistance.

worklab.ana.wingate(data, title=None, box=False, ylim=5)[source]#

Wingate test analyse. Gives a plot with the power (green) and velocity (red), also prints the important performance indicators

Parameters

  • data (dict) – processed and cutted ergometer data dictionary with dataframes

  • title (str) – title of figure

  • box (bool) – prints important performance indicators on figure, default is False

  • ylim (float, optional) – sets the ylim of the graph, default is 5 ms

Returns

  • fig (matplotlib.figure.Figure)

  • outcomes (dataframe)