**Author details**

the gradient descent algorithm a realistic orientation filter with regards to sensor fusion for

Sensor fusion also requires a novel application for smartphones and portable media devices that can simultaneously record the accelerometer and gyroscope signal for the same sample. Cognition Engineering has recently developed a smartphone and portable media device application suitable for acquiring both the accelerometer and gyroscope signal in a simultaneous manner. An example of the Cognition Engineering application has been demonstrated with regards to a person with essential tremor conducting a reach and grasp task with a deep

These trends evidenced through the development of smartphones and portable media devices as wireless accelerometer and gyroscope platforms that are effectively wearable advocate the development of Network Centric Therapy. With the development of Network Centric Therapy a patient and therapist could reside hundreds or thousands of mile remote. Rather than scheduling a traditional clinical appointment, therapy exercises and evaluation could be measured and quantified by systems, such as smartphones and portable media devices as wireless accelerometer and gyroscope platforms, for the quantification of human movement. The patient in a familiar setting of choice could conduct each therapy exercise and evaluation, and the acquired data could be transmitted wirelessly through Internet connectivity as email attachments. The post-processing could apply machine learning for augmented acuity for the therapist to determine critical transition phases of the therapy prescription and optimization

Smartphones and portable media devices have been demonstrated through progressive research, development, testing, and evaluation as wearable and wireless accelerometer and gyroscope platforms for the quantification of human movement. In particular their utility has been advocated in domains, such as quantifying gait, tendon reflex response, movement disorder, and rehabilitation exercise. Experimental data can be readily transmitted through wireless connectivity to the Internet as an email attachment. Post-processing resources and the experimental location can be remotely situated anywhere in the world. Post-processing the inertial sensor signal data into a feature set enables machine learning classification. Research has demonstrated the capacity of an assortment of machine learning algorithms to achieve considerable classification accuracy for differentiating disparate human movement scenarios, such as contrasting a hemiplegic affected side to its associated unaffected side. Smartphones and portable media devices functioning as wireless accelerometer and gyroscope platforms are envisioned to facilitate the development of Network Centric Therapy, which is predicted

to radically advance the therapy and rehabilitation experience.

smartphones and portable media devices.

18 Smartphones from an Applied Research Perspective

brain stimulator in 'On' and 'Off' mode [60].

**8. Network centric therapy**

of the rehabilitation experience.

**9. Conclusion**

Robert LeMoyne<sup>1</sup> \* and Timothy Mastroianni2

\*Address all correspondence to: rlemoyne07@gmail.com

1 Department of Biological Sciences and Center for Bioengineering Innovation, Northern Arizona University, Flagstaff, Arizona, USA

2 Independent, Pittsburgh, PA, USA
