The body–machine interface: a pathway for rehabilitation and assistance in people with movement disorders

At the beginning of the millennium, a new frontier of neuroscience and engineering appeared in the landscape of scientific and technological research: breaking the barriers of paralysis, even in its most severe forms, by developing human–machine interfaces based on what we know about how the brain plans and control movements. If we can read the neural activity from the motor cortex and correctly guess how these activities guide the movements of our arm, we can use this information for bypassing broken neural circuits and moving a prosthetic limb to interact with the environment. This vision has created a whole new research field that we know today as neural engineering [1]. While neural engineering is a young discipline, the connection between neuro science and engineering is much older. One of the founders of computer science, and one of the inventors of the digital computer, John von Neumann, was driven by the goal of creating an artificial brain [2]. It is somewhat ironic that in later times the so-called ‘von Neumann’ architecture of computers has been taken as a model of ‘nonbiological’ or even ‘antibiological’ architecture, because of its separation between processing and memory. Another giant of that time, around the time of World War II, is Norbert Wiener who set the basis for the control theory or cybernetics, guided by curiosity for biological control mechanisms [3]. Another branch of science and engineering that both influenced and was influenced by the interest in the brain is information theory. This fruitful interaction has followed different pathways, from the neuron model of Hodgkin and Huxley [4] to the development of artificial intelligence between the 1960s and the 1980s [5]. In the most recent developments, the interaction between engineering and biology has moved from understanding and imitating the brain, to the concept of interfacing with the brain. Moreover, early research in understanding movement control and decision-making also borrowed heavily from the information theory. Principles such as Fitts’ Law and Hick’s law describe the way information is processed by the brain and predict the timing of actions and decisions. These principles now form the basis for bioengineering design in fields that involve the integration of humans and machines, such as human–computer interaction. In this editorial, we focus on recent developments in the field of body–machine interfaces (BMI). The acronym BMI has traditionally been used to indicate ‘brain– machine interfaces’. Here, we use it in what we see as a broader scope, with ‘B’ standing for ‘body’ [6]. The first element of a The body–machine interface: a pathway for rehabilitation and assistance in people with movement disorders