Therapy Session

Q&A

How to Record Training Data with the LokomatPro, Software Version 6.5

Many therapists want numerical data from training sessions for research or clinical applications. The Lokomat offers a recording function that records biomechanical and technical signals in every session to monitor your patients’ progress.

With software version 6.5 the data are no longer automatically recorded; to record follow the procedure below:

  1. Select the icon System Settings on the bottom of the main menu of the software.
  2. Select SYSTEM SETTINGS in the Lokomat options.
  3. Select CONFIGURATION on the bottom of the page.
  4. Check the box “Record all signals for each session”.
  5. The system will ask you to restart the software (Lokocontrol). Press “OK” to restart.

The data recorded during training are saved by default in D:\Hocoma\Recorder as text files called “Recording_YYMMDD_HHMMSS.txt”. The second half of the file name is a timestamp with two digits for Year, Month, Day, Hour, Minute and Second.

There are many applications that will open the recording .txt file but many therapists use Microsoft Excel for this purpose. Below is a brief instruction on how to open your recorded data in Excel:

  1. Open a Blank workbook in Excel
  2. Select Data > From Text/CSV
  3. Find and select desired Recording .txt file
  4. Click “Import”
  5. Select in a preview the delimiter Semicolon
  6. Press “Load”.

Now the data are ready to be viewed and analyzed.

 

Download the Overview of the Recorded Signals in Lokocontrol V6.5 here
Q&A

Which Type of Information Regarding Patient Performance can I Visualize on the Armeo?

Would you like to quantify, monitor and visualize information regarding your patient’s performance and activity during Armeo therapy? With the Armeo 2.x software, there are multiple levels of information you can retrieve, from basic results displayed on the screen, to more complex research features. Please consider that some features are intended exclusively for research purposes.

User Feature Content
All users On-screen scoring Info displayed on the screen during and after exercises includes:

  • Exercise time
  • Score
  • Top score
  • Feedback on activity level (i.e. sparkling etc.)
All users Patient Reports

PDF format

 

 

See User Manual Chapter 4, Section 4: Reporting.

The Patient Report is a therapy record which includes the following:

  • Therapy summary: here you have a summary of all patient sessions in terms of duration and therapy goals.
  • Assessment results:
    • ArmeoSpring –> AROM (range of motion in 1D), AMOVE (range of motion in 3D) and AGOAL (gross coordination)
    • ArmeoPower –> AROM (range of motion in 1D), AMOVE (range of motion in 3D) AGOAL (gross coordination), and AFORCE (torque)
  • Exercise results: for each selected patient session you will see the scoring of the exercise and the time the patient played.
  • Session results: here you will see for each selected patient session the Arm weight support (forearm and upper arm) and the reach results.
All users Patient Reports in a Spreadsheet (XLS or CSV ) format* Enables to export patient reports in the XLS/CSV format, which can be imported to Microsoft Excel or similar software such as Matlab for further data analysis and visualization. The reports will contain all information from the PDF patient reports, and can be exported by clicking on a specific icon (see User Manual Chapter 4, section 4, and page 66).

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Clinical Researcher
(all devices)
Research Output**

 

 

The research output enables you to capture patient movements in terms of hand trajectories and joint angles as well as events that are triggered in exercises or assessments. Thus, these log files enable you to recover the full interaction of a patient and an exercise or assessment. Contact clinical.research@dih.com for more detailed information.

 

Advanced Options for Scientific Researchers

Please contact us at clinical.research@dih.com for additional advanced interface options that are available for research teams with their own software development capabilities.

*Available for Armeocontrol 2.2 onwards. Please contact your Hocoma Sales representative to schedule an upgrade.

**Please note these features are research features, which are not part of standard Armeo delivery and are provided without any guarantee and further support.

L-STIFF: LokomatPro Assessment Tool

Have you ever performed Lokomat L-STIFF? Do you want to learn more about it? Lokomat L-STIFF provides you a reliable tool to measure patient leg stiffness (Cherni et al., 2019).

What is measured?

L-STIFF measures the mechanical resistance to displacement so called stiffness of the hip and knee joint during passive flexion and extension movements. This measurement is performed at three different speeds: 30°/s, 60°/s and 120°/s for the knee and 22.5°/s, 45°/s and 90°/s for the hip. The movement pattern is preset in the software. The range of motion can be adjusted by the therapist according to the patient’s abilities.

What conclusions can be made from the measurements?

L-STIFF can support you in understanding impairments of the patient and gives you information about the joint resistance against mechanical displacements – stiffness. Keep in mind that stiffness can be caused not only by spasticity but also by other factors such as muscle contractures, joint deformities or neuromuscular pathologies. Therefore, L-STIFF values have to be interpreted carefully and complemented with other clinical evaluations performed by educated and skilled therapists.

How do L-STIFF values compare to clinical measures of spasticity (MAS)?

L-STIFF was clinically validated by measuring both L-STIFF values and Modified Ashworth Scale (MAS) values across multiple patients. Statistically speaking, the higher the L-STIFF value, the higher the MAS value (Lünenburger et al., 2005). However, it is important to have in mind that the L-STIFF assessment does not measure spasticity or MAS values per se.

How is the L-STIFF data presented?

To see the measurements obtained from L-STIFF perform the following steps:

  1. Tap [Assessments] from the [Main Menu] or [Assessments] after ending a training session.
  2. Select the patient (if necessary).
  3. Go through the [Prepare Device] screens and lift patient (remove foot lifters).
  4. Tap L‑STIFF from the [List of Assessments].
  5. Tap [Start]. The knee and hip joints are moved alternately at three speeds (30, 60, 120°/s and 22.5, 45, 90°/s respectively) with two repetitions. The patient should be completely relaxed during these movements. The Lokomat calculates a regression line for the two measurement repetitions per movement. The L‑STIFF value in Nm/° displays the slope of the regression line and indicates how much the resistance changes depending on the angle.
  6. Save the results if you wish.

Single graphs are shown for the individual joints and movement directions of flexion and extension. The bars represent stiffness in Nm/° for each tested velocity. (Colors indicate the different velocities of the measurement.) If the L‑STIFF value is negative, it is possible that the patient actively supported the movement.

How do I ensure the concurrent validity of the L‑STIFF measurements? Recommendations on the applicability in clinical practice.

The L‑STIFF algorithm relies on assumptions about biomechanical parameters of the patient (e.g. leg mass) which are estimated from the mass (body weight) and leg lengths of the patient and a mechanical model of the Lokomat legs (friction, masses, length, etc.). This measure is considered reliable as long as the following are observed.

  • The assumptions are based on the values entered in the Lokomat Patient settings (weight, height, upper and lower leg length); therefore, always make sure these values are correct.
  • Use the same hardware settings, legs, cuffs and length settings for all measurements if you want to compare them.
  • Make sure that the straps are not readjusted between measurements.
  • The L‑STIFF assumes that the patient is in a relaxed state. If the patient is moving or co-contracting during the evaluation, it will affect the measure. Encourage the patient to relax during the measurement.
  • Make sure that the upper body position of the patient does not change between or during measurements.
  • Make sure the patient is not wearing stiff clothes (e.g. thick jeans) or very heavy shoes (heavy shoes increases the mass of the leg segment, which affects the estimation of stiffness, especially at high velocities).
  • Perform the measurement during the same stages of the training across multiple sessions.
  • Compare the values and trends across multiple sessions (ideally >3).

Is there any documentation on expected values for unimpaired subjects and/or patients with neurological impairments?

No list of reference values is available at the moment. To date we are not aware of clinical studies that compared L‑STIFF values for unimpaired subjects and patients. We are currently looking for clinics that would be interested in conducting such a study in patients with neurological impairments and work in collaboration with us to further improve the L‑STIFF software and readout.

After the measurement, I see a plot on the therapist screen. What does it represent?

Just after the measurement, if you click on Results raw data will be displayed on the therapist screen. The line graph shows the joint angle (horizontal axis) vs. resistive torque (vertical axis) when the selected joint is moved at particular speed. Please, remember than at this stage, the information displayed is raw data, and computations are not yet applied.

References

Cherni Y, et al., Intra- and inter-tester reliability of spasticity assessment in standing position in children and adolescents with cerebral palsy using a paediatric exoskeleton, Disability and Rehabilitation. 2019; 1:1-7.

Riener et al., Human-centered robotics applied to gait training and assessment, J Rehabil Res Dev. 2006; 679-94.

Lünenburger et al. Clinical assessments performed during robotic rehabilitation by the gait training robot Lokomat, Proceedings of the 2005 IEEE 9th International Conference on rehabilitation Robotics. 2005; 345–348.

Report Example