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The core of the product is based on Applied Behaviour Analysis (ABA), which is a leading research-based methodology that has proven to bring about a significant change in the behavior of people with cognitive disorders.
Application that supports the therapy of cognitive deficits
for patients after stroke or craniocerebral trauma
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What is ABAStroke?
ABAStroke is a company from the MedTech industry that develops digital therapeutic tools for stroke patients who require long-term neuropsychological rehabilitation. The ABAStroke innovation is based on three pillars:
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The system dynamically adapts to the needs of patients thanks to machine learning algorithms.
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It is designed for mobile devices, thanks to which patients an experience effective therapy anywhere and at anytime, without the presence of a specialist, and to a greater extent than is offered by the traditional healthcare system.
Why ABAStroke?
Healthcare systems in many EU countries are able to provide fairly good healthcare services, but usually only at the beginning of basic rehabilitation. A huge gap in care appears when patients return home. Due to the lack of neuropsychologists, further rehabilitation is strongly limited to private treatment.
The aging of the population is leading to more strokes and the problem will be more worrying in the years to come. Urgent action is needed, and we firmly believe that ABAStroke, a well-made DTX based on ABA, is the right solution for overcoming this challenge.
About the product
The ABAStroke application was created with those adult people in mind that struggle with cognitive deficits resulting from a stroke or craniocerebral trauma.
The tool is designed in such a way as to enable the patient to start working at a level adequate to his or her deficits and available resources. For the purposes of the application, we created a series of specially developed tasks that examine the user's level of advancement in a given cognitive function. This solution maintains the patient's existing capabilities while - at the same time - focusing on the most important problems in the field of cognitive functioning.
Scientific grounds
The foundation on which ABAStroke is based is theApplied Behavior Analysis (ABA)
It is a scientific discipline that uses the laws governing behavior to solve problems that are important from the point of view of society. It is widely used in the rehabilitation of people after stroke, in terms of such functions as shaping independence, emotional control, and motivation. The experience of behavioral therapists as well as the knowledge derived from behavioral research suggest that ABA may serve as a tool that effectively supports the rehabilitation of cognitive functions in stroke patients.
ABAStroke applies behavioral laws to maximize success in terms of the rehabilitation of cognitive functions, and to shape regularity in patients' independent work.
One feature of the Applied Behavior Analysis is the individualization of the approach to the patient.
It is possible thanks to the use of tools aimed at adjusting the application to the patient's abilities. Before starting work with a given program, the patient undergoes a preliminary training session (the so-called pretest) in order to reliably assess the level of his skills, and then to individually adjust the level of difficulty.
After passing the pre-test, the patient starts working with the application within the appropriate gameplay mode, during which the level of difficulty smoothly adapts to the patient's progress or errors. The design of the game mode is based on the Discrete trial training (DTT) derived from Applied Behavior Analysis. It is a way of learning that allows for the division of skills into small, easy-to-learn portions. It then makes use of reinforcement, prompts, and repetitions in order to maximize the success of patients and effective learning.
The motivational system created in ABAStroke, based on reinforcement, visualization of progress and rewards, also aims to create positive associations among patients and encourage them to work regularly.
Patient-friendly design
The graphic design limits the impact of unnecessary distractors on the patient's work.
The layout of the boards is clear, and the colors make it clear and easy on the eyes. The tool communicates with the user using the teacher's commands supported by written text and pictograms in a size adapted to mobile devices that make use of touch screens. The interface is friendly to users who are visually impaired, hard of hearing or have other problems related to communication.
Research
Strokes are becoming a growing problem in an aging society, and post-hospitalization therapy can be not only long but also extremely expensive. Similarly, the certification process of professionals (including behavioral therapists) is time-consuming and resource-intensive. In practice, this means that not every patient that needs treatment will be able to receive it. The latest technologies combined with science, like Applied Behavior Analysis, can be the hope for solving this difficult situation.
Applied Behavior Analysis (ABA) is the foundation on which ABAStroke is built. It is a branch of psychology that deals with behavior and the environmental variables that affect it. It focuses on using the laws governing behavior to achieve three basic goals:
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Developing desired behavior
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Reducing unwanted behavior
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Generalization
The applied behavior analysis is used in working with people who experienced brain injuries and strokes, mainly as a therapy aimed at improving the behavior, habits, mood and general well-being of patients, as well as teaching them techniques that compensate for cognitive deficits.
One of the basic and best described learning techniques derived from SAZ is the discrete trial training (DTT). This method has a very specific approach to learning, which translates directly into the high effectiveness of DTT. It is based on dividing the skill that is to be learned into smaller parts, and then teaching those parts in the form of separate trials, in which the beginning and the end of learning a given portion of skills are clearly highlighted. The effectiveness of learning based on the method of extracted trials has been proved.
The use of prompts and the division of skills into smaller parts allow to maximize the patient's success, and reinforcements are a consequence that clearly translates into an increase in the probability of giving the right answer in the future. Well-designed learning combined with attention to generalization can successfully lead to a permanent mastery of the presented material and to the transfer of the effects of therapy to other environments.
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