Early Prediction of Human Motion

1. EARLY PREDICTION OF HUMAN MOTION OF
PARKINSON’S AND STROKE PATIENTS TO
IMPROVE HUMAN-ROBOT COLLABORATION TO
PERFORM SIMULTANEOUS MANIPULATION
TASKS EFFICIENTLY.
Abdullahi Chowdhury
Federation University Australia

2. HUMAN-ROBOT INTERACTION
 At the early stage of Human-Robot Interaction (HRI), a robot was considered only
as a tool which performs some simple physical tasks on command.
 From the past few decades, HRI has focused on Human-Robot collaboration that
involves a robot interacting with a human in real environment, requiring
robustness and seamless interactions [1].
 Robots have been accepted as useful substitute to human efforts in many areas
of activities. In the modern industrial environment, robot enhances the efficiency,
reduces stress and fatigue; and results in less workload to the workers [2].

3. PARKINSON’S AND STROKE DISEASE
 Alzheimer and Parkinson’s diseases (PD) are the two most common
neurodegenerative disorders among the elderly population [3].
 According to Parkinson’s Australia, approximately 30 patients are
diagnosed with Parkinson’s every day in Australia over last 6 years the
number of Parkinson’s patients increased by 17% [4].
 Another major cause of neurological disability is stroke . National
Stroke Foundation Australia advised 1 in every 6 people is in risk of
having stroke [5-6].

4. ASSISTIVE ROBOTS
 To provide appropriate support to this huge number of diseased
population an extremely smart technology need to be developed.
 Assistive Robot (AR) can certainly be very effective in managing this
huge number of patients needing both physical and psychological
support.
 Application of robotics in this field is encouraged for simplicity of
treatment, lack of side effects and positive support from patients.
Robotic assisted devices have been used for several areas in
neurological disorder in last few years [7].

5. ASSISTIVE ROBOTS (CONT…)
 Assistive Robots were designed to provide different forms of mobility
aids such as intelligent walkers , wheel chairs or exoskeletons .
 Recent research works were limited to performing the test aiming to
provide mainly physical assistance to the patients.
 No proper indication was provided the development of the algorithm
to increase the performance of better patient-robot interaction

6. SOCIAL ASSISTIVE ROBOTS
 A study by Matarić et. al., [8] suggested that the Socially Assistive Robots (SAR) are
well received among the stroke survivors.
 SAR was to prescribe therapeutic movement, record patient’s response in therapy
and report to therapist.
 Pilot study also supports that physically embodied and co-located robots have
greater acceptance among patients in contrast to virtually simulated agents.
 A follow up study of these researchers show that, mirroring user personality in
robots improves task performance in rehabilitation process.
 However this report has lacks of information about how robots will adopt the
difference of patients need depending on their age, cultural values and individual
preferences.

7. ADOPTION OF SOCIAL BEHAVIOUR
 Teaching social behavior in real time remains an open challenge in Robotics.
 Sometimes autonomous robots can recognize social behavior in real-time but a
robot’s exhibited behavior has to comply with social norms.
 The future research in SAR in Parkinson's disease could investigate and analyze the
clinical benefits of robotics with Parkinson’s and stroke patients with enhanced pro-
social behavior.
 This includes most time spent on therapeutic task and robot-patient repetition of
therapeutic interaction outside of therapist-patient session.

8. FURTHER RESEARCH
 Most of the existing AR or SAR systems have limited capabilities of improving the human
like nature and lacks self-education process in the complex and uncertain real world.
This raises several important research questions:
 Can SAR be more socially intelligent? Can the existing SAR interact with the neurological
patient in real life environment by adopting and learning from working in uncertain
conditions?
 Can SAR upgrade itself in a regular basis as per the change of the patient’s need?
 While working without support of human being, can SAR observe the body language of
the patient and adjust its behavior according to patient’s mood?
 Can SAR simultaneously do multiple tasks like providing physical support to increase
mobility, monitor the patient’s health conditions, update patient’s electronic health record
to pass the information to the relevant doctor remotely and receive updated health
information from doctor to change routine duties?

9. RESEARCH AIM
 The research specific objectives include:
 To design and develop Vision based tracking system for tracking, monitoring and
analysing the mobility of Parkinson's and Stroke Patient.
 To design deictic Gesture monitoring and analyzing system to that SAR becomes
more comfortable social partner for Parkinson’s and stroke patient than current AR.
 To design an effective and socially interactive robotics that provides companionship,
monitoring care, encouragement in rehabilitation exercises and social meditation.

10. REFERENCES
 [1]Mutlu, B.; Terrell, A.; and Huang, C. 2013. Coordination mechanisms in human-robot collaboration. In ACM/IEEE Intl.
Conf. on Human-Robot Interaction (HRI) – Workshop on Collaborative Manipulation, PP 1–6.
 [2] Heyer, C. 2010. Human-robot interaction and future industrial robotics applications. IEEE/RSJ International
Conference, 2010, PP. 4749–4754. DOI: 10.1109/IROS.2010.5651294
 [3] Lökk, J., & Fereshtehnejad, S. M. (2013). Managing palliative care in Parkinson's disease from diagnosis to end-stage
disease: what the clinician should know. Neurodegenerative Disease Management, 3(2), 169-183.
 [4] Parkinson’s Australia Inc, 2014. Annual Report 2013-2014. Accessed from URL:
http://www.parkinsons.org.au/docs/AnnualReport_2014.pdf , last accessed on 01/11/2016
 [5] Forster A, Brown L, Smith J, House A, Knapp P, Wright JJ, Young J. 2012. Information provision for stroke patients and
their caregivers. Cochrane Database of Systematic Reviews 2012, Issue 11. Art. No.: CD001919. DOI:
10.1002/14651858.CD001919.pub3.
 [6] National Stroke Foundation, 2014, Join the fight against stroke. Accessed from URL:
http://strokefoundation.com.au/get-involved/fight-stroke/join-fight/ last accessed on 01/11/2016
 [7] Sale P, Franceschini M, Waldner A, Hesse S: Use of the robot assisted gait therapy in rehabilitation of patients with
stroke and spinal cord injury. Eur J Phys Rehabil Med 2012, 48(1): PP 111–121.
 [8] Matarić M , Adriana T , Carolee W. , Jon E., 2009. Socially Assistive Robotics for Stroke and Mild TBI Rehabilitation ,
Stud. Health Technol. Inform. 45, PP: 249-62.