Brain machine interfaces (BMI) are rehabilitation tools in which neural functions, such as walking talking, hearing and seeing are modulated through feedback that is triggered by either decoded external percepts or brain activities. Some of the major challenges of BMI as rehabilitation tools involve physiological signal analysis. To overcome these challenges, signals as well as sensing devices that clearly distinguish various states in patients across time and condition are required. In sensing for BMI, characteristics like implantability, spatio-temporal resolution and invasiveness are essential. Sensing in BMI is required to either control perception to the brain or actuation from the brain. Hence, the review focusses on those that control neuro-motor functions by using brain activity to ameliorate, mitigate or restore bodily function in patients with disabilities. In addition, the review proposes future perspectives on sensing for BMI. Even with the surge in research on BMI, the major challenge still remains translating research to real-life applications. These transitions have mainly been hindered by limitations in sensing technology which this work provides more insight into.
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