Study of integrated neuro-motor rehabilitation system based on User Centered Design

1. Study of integrated neuro-motor rehabilitation system based on User Centered Design Roberto Sironi, Paolo Perego, Riccardo Lavezzari, Giuseppe Andreoni ACKNOWLEDGMENT This work has been supported by Think&Go partners Polimi, ABMedica, Idrogenet, Fondazione Cariplo, Univerlecco, Villa Beretta, CNR

2. BRAIN COMPUTER INTERFACE Brain Computer Interfaces (BCIs) are direct technological interfaces between the brain and the computer, i.e. system capable of measuring and processing brain activity. >Usually BCI are based on EEG, The most reliable and cheapest input method. >BCI researchers usually focus on performance and usability without taking into account the ergonomics and design aspects like wearability and comfort of the hardware interface. . B A

3. Goal: Develop an integrated system for neuro-motor rehabilitations - glove and BCI headset - based on User Centered Design Keywords: wearability | aesthetic acceptability | user friendliness | reliability | functionality B A • A .Gloreha Glove • Glove for passive rehabilitation of patients with any hand deficiency. • It is actuated by five independent • motors. • B. EEG Headset • Headset based on EEG input method, • for detecting and monitoring the brain • activity. • EEG headset are often used in • neuro-rehabilitation process like • post-stroke rehabilitation.

4. USER CENTERED DESIGN User-centered design (UCD) is a process in which the needs, wants, and limitations of end users of a products, service or process are given extensive attention at each stage of the design process. As suggested in the UCD (User Centered Design) methodology, the design of the headset and the glove starts from the study of user experiences. The user NWD (Needs, Wants and Desires) has been collected and analyzed with and approach divided into three steps: A.INTERVIEW WITH USERS (GLOVE) B. BENCHMARKING ANALYSIS (HEADSET) C. ANTHROPOMETRIC ANALYSIS (HAND + HEAD)

5. INTERVIEWS WITH USERS_Gloreha glove Test the user experience of Gloreha rehabilitation glove, analyzing practical, experiential, meaningful and valuable aspects, including a user’s perceptions of system such as aesthetic acceptability, efficiency and ease of use. >2 patients (one male, one female) aged from 30 to 40 years old. >Participants are both affected by symptoms of post strokes: one patient with left hand hemiparesis and one patient with right hand hemi-paretic dystonia.

6. BENCHMARKING ANALYSIS_EEG headset The development of a new product requires a previous market and benchmark analysis in order to highlight the pros and cons of each product. We conducted a market analysis comparing eleven EEG headsets. Images of the selected EEG headsets. A. BrainCap, B. ActiCap, C. ActiCapXpress, D. G.gammaCap, E. Nautilus, F. Stat X Series, G. Epoc, H. Neuro Trail, I. Mynd, L. Imec, M. Neurokeeper

7. ANTHROPOMETRIC ANALYSIS FOR MAN/WOMEN ADULT HEAD AND HAND We made an anthropometrics analysis focused on hand and head measurements. In order to create different size of the headset the analysis focused on the 1th, 50th and 99th percentiles for both the sexes.

8. RESULTS: INTERVIEWS (GLOREHA) The result of previous interviews with users have been synthetized in the following key-points: >device wearability: patients prefer to have a conformation of the glove that wrap the fingers totally; >the exercises are only for the movement of the fingers; >keep concentration is fundamental during the rehabilitation exercises; >the aesthetic of the glove is not accepted (it seems a mechanical tool and not an hand); >3D software interface doesn’t represent the real movement of the hand; >the software doesn’t encourage enough the patients in terms of motivations.

9. RESULTS: BENCHMARKING • The comparative table shows the EEG Headset market goes in two main directions: • on one side there is an offer that aims to a specialized market where users are clinicians who have special needs related to detection of EEG signals • on the other side there are systems designed for consumer market where the buyers are not always clinicians or researcher, but rather a wide range of non-specialized users

10. CONCLUSIONS >The aim of the project will be the development of an integrated system for active hand rehabilitation, through robotized glove with sensors (EMG detection) and headset for detecting EEG signals. + • > The starting point is the development of a specific EEG headset following these design requirements: • HIGH VALUE OF AESTHETIC ACCEPTABILITY • ELECTRODES REPLACEMENTS • INTEGRATION WITH THE REHABILITATION GLOVE • STABILITY AND LIGHTWEIGHT • ADAPTABLE (DIFFERENT SIZES) • EASE TO USE AND HIGH SETUP SPEED • DESIGN ACCORDING TO ANTHROPOMETRY • EASE DEVICE RECHARGEABILITY

11. CONCLUSIONS >EEG HEADSET CONCEPT ELECTRONIC 8 ACTIVE DRY ELECTRODES

12. REFERENCES >Wolpaw JR, Birbaumer N, McFarland DJ, Pfurtscheller G, Vaughan TM. “Brain–computer interfaces for communication and control”, 2002, Clin Neurophysiol. 113(6), pp. 767–91. >Perego, P., Turconi, A. C., Andreoni, G., Maggi, L., Beretta, E., Parini, S., Gagliardi, C. “Cognitive ability assessment by Brain–Computer Interface: Validation of a new assessment method for cognitive abilities”, 2011, Journal of neuroscience methods, 201(1), pp- 239-250. >Sreedharan, S., Sitaram, R., Paul, J. S., & Kesavadas, C. “Brain-computer interfaces for neurorehabilitation”, 2013, Critical Reviews™ in Biomedical Engineering, 41(3). >Abras, C., Maloney-Krichmar, D., Preece, J. “User-centered design”. 2004, Bainbridge, W. Encyclopedia of Human-Computer Interaction. Thousand Oaks: Sage Publications, 37(4), pp. 445-56. >Kimitaka, K., Akihiro, I. “Fujitsu’s Activities for Universal Design”, 2004, FUJITSU Scientific & Technical Journal 41.1, pp. 3-9. >Brainproducts Acticap website. http://www.brainproducts.com >Emotiv website. https://emotiv.com >OpenBCI website. http://www.openbci.com