Arousal Response Tool for Neurological Disease

Healthy Clinical Trial

— ART_ND  

Official title:

Arousal Response Tool for Neurological Disease

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT03425877
• Other study ID #: 2016.25
• Status: Recruiting
• Phase: N/A
• First received: January 10, 2018
• Last updated: February 1, 2018
• Start date: April 22, 2017
• Est. completion date: December 31, 2018

Study information

• Verified date: February 2018
• Source: IRCCS San Camillo, Venezia, Italy
• Contact: Patrizio Sale, MD, PhD
• Phone: +393477526350
• Email: patrizio.sale[@]unipd.it
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

The present study therefore aims at studying and evaluating the state of activation by psycho-physiological, behavioral, and subjective responses of individuals with Stroke and Parkinson's disease in contexts from the gradual increase in cognitive and stress loads, in order to provide information on the possibility Use of biofeedback devices in rehabilitation contexts.Objectives: assess the psychophysical response; to describe the configuration of physiological activation patterns; to determine the interaction effect between task type and pathology; to assess behavioral response;to describe the performance; to determine the interaction effect between task type and pathology; to evaluate the subjective response; to measure the degree of awareness of your state and your performance.

Description:

The context and the environment in which we act may interact significantly with our actions and with the property of our performance, leads to alterations of arousal states and psychophysiological stress responses.

Stress has typically been defined as a state that occurs when situation's demands are inconsistent with social, psychological and biological person's resources. Stress is an adaptive response direct to optimize the available resources to cope a given situation. However, when resources demand outstrips the individual's ability, stress has negative effects (distress). Stress effects are investigated along three domains: (1) at biological and neurophysiological modifications level, (2) at behavioral performance level and finally (3) through the subjective assessment (self-report questionnaire).

Many psychological theories have taken into account the Inverted-U shape model, in which arousal and performance are mutually reliant. There is an optimal level of arousal at which performance peaks whereas, at both lower or higher level than the optimal one, performance deteriorates .

Other thesis instead explain the different responses to stress and performance modifications in terms of cognitive resources, in particular the attentive and executive ones. Therefore, the measurement of stress involves the analysis of particular bio signals which are tied tightly to arousal such as Heart Rate (HR), Galvanic Skin Response (GSR) and electromyography (EMG), to which we should add behavioral assessment, cognitive load (in a range from single task to multi-tasking execution) and subjective assessment of one's own state of stress/distress.

Motor disability caused by neurological disorder is an important issue: every years 16 millions of people all over the world are affected by stroke and currently 33 million stroke survivor are affected by a serious acquired motor disability. Almost the whole of them are subjected to serious limitations of daily living activities and require constant assistance to their relatives.

Parkinson's Disease is the most common degenerative disorder of the central nervous system after Alzheimer's disease. Incidence rate for PD is about 18 per 100.000 person-years and it's one of the most important cause of motor disabilities in adult age with stroke.

Laboratory controlled research showed that stress response could changes psychophysiological parameters and signal (HR, GSR, EMG, EEG, etc...). A recent survey by Reinkensmeyer and colleagues (Reinkensmeyer et al., 2016) point out the relevance of computational approaches in neuro-rehabilitation which provide clear information about the neuromotor rehabilitation performance and its optimization thanks to feedback originate from analysis conducted on extensive motor and electrophysiological data.

With current technologies, many of which are available at a reduced cost, we are able to supervise on-line different aspects of our behavior, first of all the motor one. Equally important are all that technological supports which controls autonomic responses. Indeed, they highlight the relevance of individual internal response in context as the neuromotor rehabilitation one.

In such scenario, several questions still need a clear answer:

1. What are the triggering states to best cope with stressful situations and tasks?

2. What level of arousal is associated with the gradual increase of cognitive difficulties while carrying out a task?

3. Can the online feedback, on the patient's activation status, guide the work of the therapists and the patients themselves?

The present study therefore aims at studying and evaluating the state of activation by psycho-physiological, behavioral, and subjective responses of individuals with Stroke and Parkinson's disease in contexts from the gradual increase in cognitive and stress loads, in order to provide information on the possibility Use of biofeedback devices in rehabilitation contexts.

1. Assess the psychophysical response;

1. Describe the configuration of physiological activation patterns.

2. Determine the interaction effect between task type and pathology.

2. Assess behavioral response;

1. Describe the performance,

2. Determine the interaction effect between task type and pathology.

3. Evaluate the subjective response.

a. Measure the degree of awareness of your state and your performance.

4. To highlight the relationships between psychophysiological patterns, behavioral performance and subjective response.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 45
• Est. completion date: December 31, 2018
• Est. primary completion date: April 30, 2018
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 25 Years and older

Eligibility

Parkinson's disease Group

Inclusion criteria:

• Diagnosis of idiopathic Parkinson's Disease according to the UK Brain Bank Criteria

Exclusion criteria:

• Mini Mental State Examination < 24;

• Inability to walk without aid (Hoen & Yahr Scale >3)

Stroke Group

Inclusion criteria:

• Ischemic attack diagnosis.

Exclusion criteria:

• Mini Mental State Examination < 24;

• Inability to walk without aid.

Healthy Subject Group

Inclusion criteria:

• Age between 25 and 80;

• Absence of neurologic disease;

Exclusion criteria:

• Mini Mental State Examination < 24.

Related Conditions & MeSH terms

• Healthy
• Nervous System Diseases
• Parkinson Disease
• Stroke

Intervention

Device:
• MS Band 2
Before starting the experiments, the subjects will be helped to wear the Microsoft® Band 2 bracelet (a smartwatch capable of recording data from over 12 sensors, including a heart rate sensor and a skin conductance sensor) and a session will be recorded Of 10 minutes at rest. After the rest period and always wearing the Microsoft® Band 2, the subjects will perform the other session of the procedure.

Behavioral:
• Emotion Assessment
The subjects will be subjected to the viewing of 21 video clips depicting 6 different emotional states belonging to the FilmStim database validated by Schaefer's studio and collaborators (Schaefer, Nils, Sanchez, & Philippot, 2010). When viewing the clip, subjects will wear the Microsoft ® Band 2 .and after each movie clip of an evaluation of the stimulus value and activation level perceived by the Self-Assessment Manikin (Bradley & Lang, 1994) questionnaire). The presentation of movie clip is randomized and does not follow a fixed effect. Between the presentation of each clip a fixed interval of 15 seconds has been inserted in order to induce artifacts and overlap of physiological signals among different emotional valence video clips.
• Single Task
The section includes three tasks which involve upper and lower extremities, and cognitive functions, associated with low cognitive and motor load for their execution. Subjects are required to perform a single task, i.e. without the simultaneous execution of other tasks. Grasping(Motor Upper Limbs): The subject is required to reach an object's dominant limb and grab it. Walking(Motor Lower Limbs): It is required to carry 10 feet of walk. Attention(Cognitive): Signal detection task. The subject is required to detect acute sound between a series of serious sounds (Oddball Paradigm).
• Dual Task
This section includes three tasks of different types (upper limb motor, lower limb motor, cognitive) that will be performed with a greater cognitive load. Elbow N-back (Dual Task Motor upper limbs): The subject is required to reconfigure the arrangement of the floppy disks on a different blade, by moving only one disk at a time and by putting a disk on another bigger disk, never on a smaller one. Walking + Nback (Dual Task Motor lower limbs): The subject is required to walk while subtracting from 100 to 3 in 3. Problem Solving (Dual Task Cognitive): The subject is subjected to a deductive logic puzzle.
• Rest
At this stage, the HR and GSR signals will be recorded during a period of rest of 10 minutes. The subjects wear a pair of headphone for reducing the environmental sound noise. Through the headphones a sound indicates to the subject when recording starts and stops. Two separate recording of 5 minutes are performed, the first is performed while keeping eyes closed The two session are presented randomly to each different subject in order to prevent a bias due to order effect .

Locations

Country	Name	City	State
Italy	Department of Neuroscience, University of Padua	Padova
Italy	IRCCS San Camillo Hospital	Venezia

Sponsors (3)

Lead Sponsor	Collaborator
IRCCS San Camillo, Venezia, Italy	Università Politecnica delle Marche, University of Padua

Country where clinical trial is conducted

Italy, 

References & Publications (16)

Arent SM, Landers DM. Arousal, anxiety, and performance: a reexamination of the Inverted-U hypothesis. Res Q Exerc Sport. 2003 Dec;74(4):436-44. — View Citation

Bradley MM, Lang PJ. Measuring emotion: the Self-Assessment Manikin and the Semantic Differential. J Behav Ther Exp Psychiatry. 1994 Mar;25(1):49-59. — View Citation

DUFFY E. The psychological significance of the concept of arousal or activation. Psychol Rev. 1957 Sep;64(5):265-75. — View Citation

Feigin VL, Forouzanfar MH, Krishnamurthi R, Mensah GA, Connor M, Bennett DA, Moran AE, Sacco RL, Anderson L, Truelsen T, O'Donnell M, Venketasubramanian N, Barker-Collo S, Lawes CM, Wang W, Shinohara Y, Witt E, Ezzati M, Naghavi M, Murray C; Global Burden of Diseases, Injuries, and Risk Factors Study 2010 (GBD 2010) and the GBD Stroke Experts Group. Global and regional burden of stroke during 1990-2010: findings from the Global Burden of Disease Study 2010. Lancet. 2014 Jan 18;383(9913):245-54. Review. Erratum in: Lancet. 2014 Jan 18;383(9913):218. — View Citation

Harrivel, A. R., Liles, C., Stephens, C. L., Ellis, K. K., Prinzel, L. J., & Pope, A. T. (2016). Psychophysiological Sensing and State Classification for Attention Management in Commercial Aviation. In AIAA Infotech @ Aerospace. Reston, Virginia: American Institute of Aeronautics and Astronautics. http://doi.org/10.2514/6.2016-1490

Kerr JH. The experience of arousal: a new basis for studying arousal effects in sport. J Sports Sci. 1985 Autumn;3(3):169-79. — View Citation

Knaepen K, Marusic U, Crea S, Rodríguez Guerrero CD, Vitiello N, Pattyn N, Mairesse O, Lefeber D, Meeusen R. Psychophysiological response to cognitive workload during symmetrical, asymmetrical and dual-task walking. Hum Mov Sci. 2015 Apr;40:248-63. doi: 10.1016/j.humov.2015.01.001. Epub 2015 Jan 23. — View Citation

Kuppens P, Tuerlinckx F, Russell JA, Barrett LF. The relation between valence and arousal in subjective experience. Psychol Bull. 2013 Jul;139(4):917-40. doi: 10.1037/a0030811. Epub 2012 Dec 10. Review. — View Citation

Kyle BN, McNeil DW. Autonomic arousal and experimentally induced pain: a critical review of the literature. Pain Res Manag. 2014 May-Jun;19(3):159-67. Epub 2014 Feb 14. Review. — View Citation

Mackersie CL, Calderon-Moultrie N. Autonomic Nervous System Reactivity During Speech Repetition Tasks: Heart Rate Variability and Skin Conductance. Ear Hear. 2016 Jul-Aug;37 Suppl 1:118S-25S. doi: 10.1097/AUD.0000000000000305. Review. — View Citation

Reinkensmeyer DJ, Burdet E, Casadio M, Krakauer JW, Kwakkel G, Lang CE, Swinnen SP, Ward NS, Schweighofer N. Computational neurorehabilitation: modeling plasticity and learning to predict recovery. J Neuroeng Rehabil. 2016 Apr 30;13(1):42. doi: 10.1186/s12984-016-0148-3. Review. — View Citation

Salehi B, Cordero MI, Sandi C. Learning under stress: the inverted-U-shape function revisited. Learn Mem. 2010 Sep 30;17(10):522-30. doi: 10.1101/lm.1914110. Print 2010 Oct. — View Citation

Schaefer, A., Nils, F. F., Sanchez, X., & Philippot, P. (2010). Assessing the effectiveness of a large database of emotion-eliciting films: A new tool for emotion researchers. Cognition & Emotion, 24(7), 1153-1172. http://doi.org/10.1080/02699930903274322

Shelgikar AV, Anderson PF, Stephens MR. Sleep Tracking, Wearable Technology, and Opportunities for Research and Clinical Care. Chest. 2016 Sep;150(3):732-43. doi: 10.1016/j.chest.2016.04.016. Epub 2016 Apr 29. Review. — View Citation

Westman, M., & Eden, D. (1996). The inverted-U relationship between stress and performance: A field study. Work & Stress, 10(2), 165-173. http://doi.org/10.1080/02678379608256795

Wiberg H, Nilsson E, Lindén P, Svanberg B, Poom L. Physiological responses related to moderate mental load during car driving in field conditions. Biol Psychol. 2015 May;108:115-25. doi: 10.1016/j.biopsycho.2015.03.017. Epub 2015 Apr 6. — View Citation

* Note: There are 16 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Galvanic Skin Response	The GSR sensor measures the conductivity of the skin between the GSR diode contact points on the other side of the clasp, raised from the battery cover.; Galvanic Skin Response data are acquired and stored in a connected device text file using a customised application able to acquire MS Band 2 GSR signal at a sample rate of 40 Hz, and expressed in microsiemens (µS).	3 hours
Primary	Heart Rate	The optical heart rate monitor of the Microsoft Band uses a light sensor to detect minor fluctuations in the wrist capillaries. The heart rate monitor is located on the back of the clasp.; Heart Rate data are continuously acquired and stored in a connected device text file using a customised application able to acquire MS Band 2 HR signal at a sample rate of 2 Hz, together with a timestamp, and expressed in heart beats per minutes (bpm).	3 hours
Primary	Valence	Valence is measured using the Self-Assessment Manikin (SAM) (Hodes, Cook & Lang, 1985) to directly assess the valence, arousal, and dominance associated in response to an object or event. SAM Valence is a self assessment 7-point likert scale which ranges from a smiling, happy figure (score: 7) to a frowning, unhappy figure (score: 1) when representing the pleasure dimension.; The scale is proposed after each stimuli is presented or task executed by the subjects, and the scores are collected through the psychology experiment design software Psychopy (Peirce, 2007), which collects also the subjects ID and the timestamp, while the band is worn by the subjects.	3 hours
Primary	Arousal	Arousal is measured using the Self-Assessment Manikin (SAM) (Hodes, Cook & Lang, 1985) to directly assess the valence, arousal, and dominance associated in response to an object or event. SAM Arousal is a self assessment 7-point likert scale which ranges from an excited, wide-eyed figure (score: 7) to a relaxed, sleepy figure (score: 1) for the arousal dimension.; The scale is proposed after each stimuli is presented or task executed by the subjects, and the scores are collected through the psychology experiment design software Psychopy (Peirce, 2007), which collects also the subjects ID and the timestamp, while the band is worn by the subjects.	3 hours