Assessment of Upper Limb Motor Performance Using an Interface With Haptic Feedback

The purpose of the study is to test an evaluation environment based on a device that has the ability to provide the user with tactile (haptic) sensations. This environment will be used to investigate how the arm movements of a healthy person are performed, and then - at a later stage - to find out whether it is possible to measure changes during musculoskeletal pain. Electrical signals produced by the brain (called electroencephalogram or EEG) will be recorded by means of electrodes on the surface of the scalp (non-invasive). In addition, the angle of the elbow joint during movement will be measured, with the intention of using objective measures to aid future evidence-based clinical decision making.

It is expected that the developed environment can be used -in the near future-, to evaluate the progression of pathologies associated with muscle pain, or to quantify the effectiveness of rehabilitation therapies.

Study Overview

• Status: Completed
• Conditions: Healthy
• Intervention / Treatment: Device: Functional test with a haptic device

Detailed Description

Experimental setup Volunteers will be received at the Center of Rehabilitation Engineering and Neuromuscular and Sensory Research (CIRINS). They will be informed, in simple terms, of the purpose of the project and the measurements that will be done during the session. The Informed Consent Form will be read to each volunteer and, if they decide to participate, they will be asked to sign a copy that will be filed in the Laboratory together with their contact information, which will be stored confidentially.

At the beginning of the session, the volunteer will be asked to sit comfortably. The EEG electrodes will then be attached using a 16-electrode cap in the standard 10-20 location, together with the exoskeleton in the position determined by the investigator. The position of the camera that will be used to follow the movements of the upper limb will also be adjusted to ensure that the movements will be within the camera's field of view.

Subsequently, the subject will be placed in its initial position: seated, with approximately 45° of shoulder abduction, 10° of shoulder flexion and 90° of elbow flexion.

Once the subject is in the proper position, they will be asked, using the implemented test interface, to perform the virtual nine-hole peg test (NHPT) in Cue Based and Self Paced variants. The volunteer will be asked to complete these tests with both hands, in order to assess whether there are differences in performance associated with the side with which the test is performed, and whether using the system is sensitive enough to detect these changes. The researcher conducting the experiment should record which test was performed with the dominant hand and which was not.

To evaluate whether the results obtained are satisfactory, they will be compared with those reported for healthy individuals.

Evaluation tests Cue-based nine-hole peg test: this test works with time or event dependent cues, dividing the test into several repetitions of the same task. Each trial starts at the same predetermined position, and consists of placing as quickly as possible a random peg in a random hole. This randomness is given in the order of the first nine attempts without repeating the peg. Then, in case of additional attempts, the order of the first nine attempts is repeated. In case of failure to complete an attempt within a certain time or placing the peg in the wrong hole, it is given as failed. The signals presented to the user are visual. The pegs change color from white (inactive) to red, which marks the peg that should move (but without giving the signal to move yet), when the peg changes to green, the movement should begin. Likewise, the hole into which the peg should be inserted is marked with the addition of a translucent light blue object. Inactive holes have no color or object inside. At the end of a repetition, the position of the pegs is reset. The starting point of each repetition of the test is marked with a translucent sphere, which is the position that the robot cursor must take before the next attempt. This object sees its position reflected along with the other elements of the virtual environment when changing hands.

Self-paced nine-hole peg test : this test gives the user the freedom to place the desired peg in the desired hole at the desired speed. This test is the most similar to the original NHPT, and ends when all nine pegs are placed in the nine holes, giving as a result the total duration of the test.

• Study Type: Observational
• Enrollment (Actual): 30

Contacts and Locations

Study Locations

• Argentina
  • Entre Ríos
    • Oro Verde, Entre Ríos, Argentina, 3100
      • Facultad de Ingeniería, Universidad Nacional de Entre Ríos

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

Healthy volunteers

Description

Inclusion Criteria:

• No history of neurological disease, chronic pain, or musculoskeletal disorders.
• Willingness and ability to fully understand the content and scope of the experiment and to comply with the instructions.
• Signature of the informed consent document.

Exclusion Criteria:

• Pregnancy.
• History of chronic pain or neuromuscular disorders.
• History of addictive behavior, defined as abuse of alcohol, cannabis, opioids or other drugs.
• History of heat sensitivity disorders.
• Presence of fever, tuberculosis, malignant tumors, infectious processes, acute inflammatory processes.
• Implantation of pacemakers or metallic prostheses.
• Use of analgesics within 24 hours prior to participation in the experiment.
• Lack of cooperation.
• Trauma of the segment to be evaluated in the last 4 weeks.
• Surgical history of the upper quadrant.
• Metabolic diseases.
• Ingestion of pain medication in the last 24 hs.

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Healthy; Healthy volunteers	Device: Functional test with a haptic device; Volunteers will complete two tests based on the Nine Hole Peg Test with a haptic device.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Movement smoothness	Smoothness of the participant movement calculated through the fourth derivative of the trajectory (jerk).	Average of 36 trials during a single experimental session with a duration of 30 minutes

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Log jerk transport	Smoothness of the peg transport trajectory, from the initial position to the hole.	Average of 36 trials during a single experimental session with a duration of 30 minutes
Log jerk return	Smoothness of the return trajectory, from the position of the hole where the last peg was inserted to the initial position of the next peg.	Average of 36 trials during a single experimental session with a duration of 30 minutes
SPARC return	Smoothness of the return trajectory, from the position of the hole where the last peg was inserted to the initial position of the next peg.	Average of 36 trials during a single experimental session with a duration of 30 minutes
Path length ratio transport	Efficiency of the peg transport trajectory, from the initial position to the hole.	Average of 36 trials during a single experimental session with a duration of 30 minutes
Path length ratio return	Efficiency of the return trajectory, from the position of the hole where the last peg was inserted to the initial position of the next peg.	Average of 36 trials during a single experimental session with a duration of 30 minutes
Velocity max. return	Maximum velocity during the return trajectory, from the position of the hole where the last peg was inserted to the initial position of the next peg.	Average of 36 trials during a single experimental session with a duration of 30 minutes
Jerk peg approach	Precision of the ballistic movement during the approach to the peg (near the end of the return and just before the beginning of transport).	Average of 36 trials during a single experimental session with a duration of 30 minutes

Collaborators and Investigators

• Sponsor: Universidad Nacional de Entre Rios
• Investigators: Principal Investigator: Rosa M Weisz, MSc. in Biomed Eng, Universidad Nacional de Entre Rios

Publications and helpful links

General Publications

• Feys P, Lamers I, Francis G, Benedict R, Phillips G, LaRocca N, Hudson LD, Rudick R; Multiple Sclerosis Outcome Assessments Consortium. The Nine-Hole Peg Test as a manual dexterity performance measure for multiple sclerosis. Mult Scler. 2017 Apr;23(5):711-720. doi: 10.1177/1352458517690824. Epub 2017 Feb 16.
• Hodges PW, Tucker K. Moving differently in pain: a new theory to explain the adaptation to pain. Pain. 2011 Mar;152(3 Suppl):S90-S98. doi: 10.1016/j.pain.2010.10.020. Epub 2010 Nov 18. No abstract available.
• Mista CA, Monterde S, Ingles M, Salvat I, Graven-Nielsen T. Reorganized Force Control in Elbow Pain Patients During Isometric Wrist Extension. Clin J Pain. 2018 Aug;34(8):732-738. doi: 10.1097/AJP.0000000000000596.
• Karos K, Meulders A, Gatzounis R, Seelen HAM, Geers RPG, Vlaeyen JWS. Fear of pain changes movement: Motor behaviour following the acquisition of pain-related fear. Eur J Pain. 2017 Sep;21(8):1432-1442. doi: 10.1002/ejp.1044. Epub 2017 Apr 25.
• Tsay A, Allen TJ, Proske U, Giummarra MJ. Sensing the body in chronic pain: a review of psychophysical studies implicating altered body representation. Neurosci Biobehav Rev. 2015 May;52:221-32. doi: 10.1016/j.neubiorev.2015.03.004. Epub 2015 Mar 14.
• Rigsby B, Reed KB. Accuracy of Dynamic Force Compensation Varies With Direction and Speed. IEEE Trans Haptics. 2019 Oct-Dec;12(4):658-664. doi: 10.1109/TOH.2019.2912375. Epub 2019 Apr 23.
• Kanzler CM, Schwarz A, Held JPO, Luft AR, Gassert R, Lambercy O. Technology-aided assessment of functionally relevant sensorimotor impairments in arm and hand of post-stroke individuals. J Neuroeng Rehabil. 2020 Sep 25;17(1):128. doi: 10.1186/s12984-020-00748-5.
• Kanzler CM, Rinderknecht MD, Schwarz A, Lamers I, Gagnon C, Held JPO, Feys P, Luft AR, Gassert R, Lambercy O. A data-driven framework for selecting and validating digital health metrics: use-case in neurological sensorimotor impairments. NPJ Digit Med. 2020 May 29;3:80. doi: 10.1038/s41746-020-0286-7. eCollection 2020.
• Schwarz A, Kanzler CM, Lambercy O, Luft AR, Veerbeek JM. Systematic Review on Kinematic Assessments of Upper Limb Movements After Stroke. Stroke. 2019 Mar;50(3):718-727. doi: 10.1161/STROKEAHA.118.023531.
• Wright DJ, Holmes PS, Smith D. Using the movement-related cortical potential to study motor skill learning. J Mot Behav. 2011;43(3):193-201. doi: 10.1080/00222895.2011.557751.
• Spuler M, Niethammer C. Error-related potentials during continuous feedback: using EEG to detect errors of different type and severity. Front Hum Neurosci. 2015 Mar 26;9:155. doi: 10.3389/fnhum.2015.00155. eCollection 2015.
• J. D. Guzmán, E. F. Fonseca, C. F. Rengifo, D. E. Guzmán, J. Londoño and E. Muñoz, "Implementación de la prueba de funcionalidad motriz de miembro superior nine-hole peg test en un entorno virtual 3D", Iberdiscap, 2017
• Ahmed T, Thopalli K, Rikakis T, Turaga P, Kelliher A, Huang JB, Wolf SL. Automated Movement Assessment in Stroke Rehabilitation. Front Neurol. 2021 Aug 19;12:720650. doi: 10.3389/fneur.2021.720650. eCollection 2021.
• Mista CA, Laugero SJ, Adur JF, Andersen OK, Biurrun Manresa JA. A new experimental model of muscle pain in humans based on short-wave diathermy. Eur J Pain. 2019 Oct;23(9):1733-1742. doi: 10.1002/ejp.1449. Epub 2019 Jul 24.
• Gatti R, Atum Y, Schiaffino L, Jochumsen M, Biurrun Manresa J. Decoding kinetic features of hand motor preparation from single-trial EEG using convolutional neural networks. Eur J Neurosci. 2021 Jan;53(2):556-570. doi: 10.1111/ejn.14936. Epub 2020 Aug 25.
• W. Wei, "Virtual reality enhanced robotic systems for disability rehabilitation," in Virtual and Augmented Reality: Concepts, Methodologies, Tools, and Applications, 2018
• S. Mahamad, S. M. Taib, and M. N. Ibrahim, "Analyzing speed accuracy trade-off in control movement mechanism with error enforcement," in Applied Mechanics and Materials, 2011.

Study record dates

Study Major Dates

• Study Start (Actual): May 9, 2023
• Primary Completion (Actual): December 14, 2023
• Study Completion (Actual): December 14, 2023

Study Registration Dates

• First Submitted: April 5, 2023
• First Submitted That Met QC Criteria: April 5, 2023
• First Posted (Actual): April 19, 2023

Study Record Updates

• Last Update Posted (Estimated): December 19, 2023
• Last Update Submitted That Met QC Criteria: December 18, 2023
• Last Verified: December 1, 2023

More Information

Terms related to this study

• Keywords: Musculoskeletal pain; Virtual environment; Haptic technology
• Other Study ID Numbers: IS003960

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: All collected IPD except video recordings.
• IPD Sharing Time Frame: The study protocol is available since the protocol registration. IPD, SAP and analytic code will be available 6 months after data collection.
• IPD Sharing Access Criteria: Open access in a public platform.
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL; SAP; ANALYTIC_CODE

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No