Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài:Using hierarchical clustering methods to classify motor activities of COPD patients from wearable sensor data | Journal of NeuroEngineering and Rehabilitation BioMed Central Research Open Access Using hierarchical clustering methods to classify motor activities of COPD patients from wearable sensor data Delsey M Sherrill1 Marilyn L Moy2 John J Reilly2 and Paolo Bonato 1 3 Address 1Dept of Physical Medicine and Rehabilitation Harvard Medical School Spaulding Rehabilitation Hospital Boston MA USA 2Dept of Medicine Harvard Medical School Brigham and Women s Hospital Boston MA USA and 3The Harvard-MIT Division of Health Sciences and Technology Cambridge MA USA Email Delsey M Sherrill - dsherrill@ Marilyn L Moy - mmoy@ John J Reilly - jreilly@ Paolo Bonato - pbonato@ Corresponding author Published 29 June 2005 Received 07 June 2005 Journal of NeuroEngineering and Rehabilitation 2005 2 16 doi 86 1743- Accepted 29 June 2005 0003-2-16 This article is available from http content 2 1 16 2005 Sherrill et al licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Background Advances in miniature sensor technology have led to the development of wearable systems that allow one to monitor motor activities in the field. A variety of classifiers have been proposed in the past but little has been done toward developing systematic approaches to assess the feasibility of discriminating the motor tasks of interest and to guide the choice of the classifier architecture. Methods A technique is introduced to address this problem according to a hierarchical framework and its use is demonstrated for the application of detecting motor activities in patients with chronic obstructive pulmonary disease COPD undergoing pulmonary rehabilitation. Accelerometers were used to collect data .
