Intelligent Brain Computer Interfacing BCI based personalized healthcare system of neuro rehabilitation
Brain-Computer Interfaces (BCIs) have gained popularity over the last one decade, due to its success in neuro-rehabilitation for people with mild to severe disabilities which leads to partial or full body paralysis (e.g. Spinal-cord injury (SCI), Amyotrophic lateral sclerosis (ALS)), all aro
2025-06-28 16:33:17 - Adil Khan
Intelligent Brain Computer Interfacing BCI based personalized healthcare system of neuro rehabilitation
Project Area of Specialization Internet of ThingsProject SummaryBrain-Computer Interfaces (BCIs) have gained popularity over the last one decade, due to its success in
neuro-rehabilitation for people with mild to severe disabilities which leads to partial or full body
paralysis (e.g. Spinal-cord injury (SCI), Amyotrophic lateral sclerosis (ALS)), all around the world. BCI
is a rapidly evolving field that seeks direct interaction between the human brain and machines. In this
proposal, we will develop An Intelligent BCI based Personalized Healthcare System for NeuroRehabilitation for people living with disabilities, for their neuro-rehabilitation and will also act as an
auxiliary control to operate other devices to perform activities of daily livings (ADLs) e.g. robotic
wheelchairs, tilt / recline hospital beds, remote-controls for TV, keyboards for PCs, smartphones/tablets,
and video-game controllers. We envisage that this will help people living with paralysis, in bringing
back to their lives and perform normal ADLs. The proposed system will be integrated with a neurorehabilitation system for physical rehabilitation of patient’s body parts (both upper and lower) and
adaptively tune towards their desired neuro-rehabilitation functional goals. Also, the proposed system
can be used as a generalized interface between the patient and other gadgets relating to ADLs. This is a
newly emergent concept of self-management of disease, ultimately lifting an ever-increasing burden of
care from clinicians and carers of the Pakistani healthcare system. The neural activity of the person living
with disability will be recorded using electroencephalogram (EEG) electrodes (via EEG Cap). The
signals obtained from EEG activity will be filtered and a machine learning algorithm (both linear and
non-linear) e.g. Principal Component Analysis (PCA), Independent Component Analysis (ICA) and
IsoMap will be used to recognize (via pattern classification) the desired activities of the person. The
classification application will then be used to learn and to decipher the patient's desired movements and
to encode control signals for external device control. Visual feedback will play an important role in the
fine-tuning or adjustments of the neural activity for the patients. The development of a BCI-PD for neurorehabilitation and controlling ADL devices will help the patient in facilitating or compensating the upper
or lower body movements resulting in enhancement of functional recovery and neuroplasticity to
perform actions which are not possible without clinician’s or career’s help.
The overall objective of the project is to develop, demonstrate and initiate exploitation of new open and
modular platform that enable patients living with disabilities to self-manage their ADLs and pathologies
by using BCI based system capable to perform diagnosis, prognosis and suggest neurorehabilitation
therapy. The proposed system will guide the user, via advice, in choosing action aimed at reducing the
impact of degenerative disease or executing an assisted and monitored rehabilitation or preventive
protocol continuously counselled by indications deriving from medical and neurorehabilitation
knowledge. More specifically the objectives are:
- To develop An Intelligent BCI based Personalized Healthcare System for Neurorehabilitation in consistent with certified medical guidelines of the considered pathologies capable to provide the patient with advice and to cooperate with him for a disease self-management.
- Adapting existing BCI and other wearable technology to monitor the clinical case of the
patient and produce inputs for the decisional process aimed at implementing neurorehabilitation
protocol. - To develop a multistage software, representing the prediction capabilities of the platform and implementing existing models.
Starting point will be the findings from related previous (European and Australian) research activities and additional detailed analysis of the specific user requirements for the proposed system. This task will generate the criteria for the eligibility of the patients to be treated by conservative methods selected for the project. Next task will begin with an analysis of the state of the art of infrastructure technologies and development tools. Based on the user requirements and use cases, functional specifications will be derived. Subsequently, these will be translated into technical specifications and definitions for the proposed system architecture. After that we will develop a multimodal sensing (with EEG cap, and wearable sensing) platform to assess selected kinematic and physiological quantities that are essential for monitoring and influencing performance in physical disabilities disorders. First, available BCI technology and wearable sensing will be evaluated and compared to achieve the quantities identified on clinical and biomechanical insights and the outcome of the requirements analysis. Second, a minimal multimodal sensing system will be developed to assess these quantities during ambulatory and daily life conditions. This will result in an action patterns recognition, upper-limb posture analysis, and sensory module specific for the considered disorder. Finally, the minimal multimodal sensing systems will be technically validated compared to reference laboratory systems to evaluate their performance in assessing the selected kinematic and physiological quantities. Next objectives to be achieved will be the design and the realization of the user interfaces, the professional interface and the management of the communication between the portable device and sensors and the remote server placed in clinic/hospital. The user interface must be friendly and easy to use by the patients, has to create engagement and empower the self-management of their condition by means of graphic and multimedia resources which help to understand the user. The professional interface, running on a remote server, must be capable to present data mining outputs used by the clinicians to have clinical cases in real time and provide feedback and recommendations to the patients. It should be also able to present to the clinicians, predictions, about: the health outcome, estimates of costs and quality of life.
Benefits of the ProjectThe proposed project would promote better monitored physical disabilities management (functioning
and neuro-rehabilitation) in Pakistani domestic care and clinical situations. Following will/can be the beneficiaries of the project:
- Pakistan Society for the rehabilitation of the disabled (PSRD)
- Other than PSRD following is the list of beneficiaries of this project:
- Academic and Industrial researchers.
- Doctors and Medical staff.
- Hospitals, Clinics, and Rehabilitation Centers.
- Paralyses, Stroke and other patients with functional disabilities due to brain injuries.
- Health Sector, IT Industry and Community Development Centers.
Final project deliverable will include the following:
- Mobile User Interface definition and implementation.
- Professional User Interface definition, implementation and data mining presentation.
- Data Communication format and protocol.
- Sensing systems developed such as image/visualization or wearable accessories that will constitute the sensing modules of the BCI-PD platform.
- Algorithms implementing, diagnostic and predictive models.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 76000 | |||
| EEG Sensor Cap | Equipment | 1 | 40000 | 40000 |
| Arduino Boards | Equipment | 2 | 1000 | 2000 |
| Programing Gateway for Sensors | Equipment | 1 | 4000 | 4000 |
| Wi-Fi Modules | Equipment | 2 | 1000 | 2000 |
| BLE Modules | Equipment | 2 | 1000 | 2000 |
| Wi-Fi Router | Equipment | 1 | 2000 | 2000 |
| Android Smartphone For Mobile Interface | Equipment | 1 | 18000 | 18000 |
| Wires, Resistors, Connectors etc | Miscellaneous | 1 | 6000 | 6000 |