Step Detection and Activity Recognition Accuracy of Seven Physical Activity Monitors
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{"title"=>"Step detection and activity recognition accuracy of seven physical activity monitors", "type"=>"journal", "authors"=>[{"first_name"=>"Fabio A.", "last_name"=>"Storm", "scopus_author_id"=>"56572448700"}, {"first_name"=>"Ben W.", "last_name"=>"Heller", "scopus_author_id"=>"7006583311"}, {"first_name"=>"Claudia", "last_name"=>"Mazzà", "scopus_author_id"=>"7006089519"}], "year"=>2015, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84925583251", "pui"=>"603271611", "doi"=>"10.1371/journal.pone.0118723", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "sgr"=>"84925583251", "pmid"=>"25789630"}, "id"=>"34d76a79-12e0-39aa-8916-ea6a74078fb6", "abstract"=>"The aim of this study was to compare the seven following commercially available activity monitors in terms of step count detection accuracy: Movemonitor (Mc Roberts), Up (Jawbone), One (Fitbit), ActivPAL (PAL Technologies Ltd.), Nike+ Fuelband (Nike Inc.), Tractivity (Kineteks Corp.) and Sensewear Armband Mini (Bodymedia). Sixteen healthy adults consented to take part in the study. The experimental protocol included walking along an indoor straight walkway, descending and ascending 24 steps, free outdoor walking and free indoor walking. These tasks were repeated at three self-selected walking speeds. Angular velocity signals collected at both shanks using two wireless inertial measurement units (OPAL, ADPM Inc) were used as a reference for the step count, computed using previously validated algorithms. Step detection accuracy was assessed using the mean absolute percentage error computed for each sensor. The Movemonitor and the ActivPAL were also tested within a nine-minute activity recognition protocol, during which the participants performed a set of complex tasks. Posture classifications were obtained from the two monitors and expressed as a percentage of the total task duration. The Movemonitor, One, ActivPAL, Nike+ Fuelband and Sensewear Armband Mini underestimated the number of steps in all the observed walking speeds, whereas the Tractivity significantly overestimated step count. The Movemonitor was the best performing sensor, with an error lower than 2% at all speeds and the smallest error obtained in the outdoor walking. The activity recognition protocol showed that the Movemonitor performed best in the walking recognition, but had difficulty in discriminating between standing and sitting. Results of this study can be used to inform choice of a monitor for specific applications.", "link"=>"http://www.mendeley.com/research/step-detection-activity-recognition-accuracy-seven-physical-activity-monitors", "reader_count"=>160, "reader_count_by_academic_status"=>{"Unspecified"=>4, "Professor > Associate Professor"=>5, "Librarian"=>2, "Researcher"=>27, "Student > Doctoral Student"=>8, "Student > Ph. D. Student"=>42, "Student > Postgraduate"=>5, "Student > Master"=>30, "Other"=>13, "Student > Bachelor"=>14, "Lecturer"=>5, "Lecturer > Senior Lecturer"=>1, "Professor"=>4}, "reader_count_by_user_role"=>{"Unspecified"=>4, "Professor > Associate Professor"=>5, "Librarian"=>2, "Researcher"=>27, "Student > Doctoral Student"=>8, "Student > Ph. D. Student"=>42, "Student > Postgraduate"=>5, "Student > Master"=>30, "Other"=>13, "Student > Bachelor"=>14, "Lecturer"=>5, "Lecturer > Senior Lecturer"=>1, "Professor"=>4}, "reader_count_by_subject_area"=>{"Unspecified"=>15, "Agricultural and Biological Sciences"=>9, "Arts and Humanities"=>2, "Business, Management and Accounting"=>1, "Computer Science"=>27, "Engineering"=>21, "Nursing and Health Professions"=>13, "Biochemistry, Genetics and Molecular Biology"=>2, "Medicine and Dentistry"=>38, "Neuroscience"=>3, "Sports and Recreations"=>12, "Psychology"=>7, "Social Sciences"=>9, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>38}, "Social Sciences"=>{"Social Sciences"=>9}, "Sports and Recreations"=>{"Sports and Recreations"=>12}, "Psychology"=>{"Psychology"=>7}, "Unspecified"=>{"Unspecified"=>15}, "Arts and Humanities"=>{"Arts and Humanities"=>2}, "Engineering"=>{"Engineering"=>21}, "Neuroscience"=>{"Neuroscience"=>3}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>9}, "Computer Science"=>{"Computer Science"=>27}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>13}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>2}}, "reader_count_by_country"=>{"Korea (South)"=>1, "United States"=>3, "United Kingdom"=>3}, "group_count"=>13}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1961743"], "description"=>"<p>Summary of the activities performed during the step detection protocol, their duration and the step count (as obtained by the OPAL sensors) for each walking speed.</p>", "links"=>[], "tags"=>["Step detection accuracy", "pal", "opal", "Sensewear Armband Mini", "step count", "activpal", "speed", "activity recognition protocol", "sensor", "Nike", "percentage", "ADPM", "Activity Recognition Accuracy", "task duration.The Movemonitor", "Tractivity", "inc", "Angular velocity signals", "step count detection accuracy", "Fuelband", "Physical Activity Monitors"], "article_id"=>1343424, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Fabio A. Storm", "Ben W. Heller", "Claudia Mazzà"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0118723.t003", "stats"=>{"downloads"=>2, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_of_the_activities_performed_during_the_step_detection_protocol_their_duration_and_the_step_count_as_obtained_by_the_OPAL_sensors_for_each_walking_speed_/1343424", "title"=>"Summary of the activities performed during the step detection protocol, their duration and the step count (as obtained by the OPAL sensors) for each walking speed.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-03-19 03:31:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/1961741"], "description"=>"<p>Sample Characteristics of the study group (mean ± SD).</p>", "links"=>[], "tags"=>["Step detection accuracy", "pal", "opal", "Sensewear Armband Mini", "step count", "activpal", "speed", "activity recognition protocol", "sensor", "Nike", "percentage", "ADPM", "Activity Recognition Accuracy", "task duration.The Movemonitor", "Tractivity", "inc", "Angular velocity signals", "step count detection accuracy", "Fuelband", "Physical Activity Monitors"], "article_id"=>1343422, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Fabio A. Storm", "Ben W. Heller", "Claudia Mazzà"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0118723.t001", "stats"=>{"downloads"=>2, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sample_Characteristics_of_the_study_group_mean_177_SD_/1343422", "title"=>"Sample Characteristics of the study group (mean ± SD).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-03-19 03:31:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/1961738"], "description"=>"<p>The figure shows the mean percentage error (MPE) during slow, self-selected and fast walking speed trials for all the sensors included in the study. Error bars are mean ± SD.</p>", "links"=>[], "tags"=>["Step detection accuracy", "pal", "opal", "Sensewear Armband Mini", "step count", "activpal", "speed", "activity recognition protocol", "sensor", "Nike", "percentage", "ADPM", "Activity Recognition Accuracy", "task duration.The Movemonitor", "Tractivity", "inc", "Angular velocity signals", "step count detection accuracy", "Fuelband", "Physical Activity Monitors"], "article_id"=>1343419, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Fabio A. Storm", "Ben W. Heller", "Claudia Mazzà"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0118723.g003", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_of_MPE_for_the_7_PAMs_included_in_the_study_/1343419", "title"=>"Summary of MPE for the 7 PAMs included in the study.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-03-19 03:31:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/1961746"], "description"=>"<p>Data is presented as percentage of the total duration of the activity (mean ± SD).</p><p>Classification of the performed activities for the Movemonitor sensor.</p>", "links"=>[], "tags"=>["Step detection accuracy", "pal", "opal", "Sensewear Armband Mini", "step count", "activpal", "speed", "activity recognition protocol", "sensor", "Nike", "percentage", "ADPM", "Activity Recognition Accuracy", "task duration.The Movemonitor", "Tractivity", "inc", "Angular velocity signals", "step count detection accuracy", "Fuelband", "Physical Activity Monitors"], "article_id"=>1343427, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Fabio A. Storm", "Ben W. Heller", "Claudia Mazzà"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0118723.t006", "stats"=>{"downloads"=>2, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Classification_of_the_performed_activities_for_the_Movemonitor_sensor_/1343427", "title"=>"Classification of the performed activities for the Movemonitor sensor.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-03-19 03:31:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/1961745"], "description"=>"<p>Data is presented as percentage of the total duration of the activity (mean ± SD).</p><p>Classification of the performed activities for the ActivPAL sensor.</p>", "links"=>[], "tags"=>["Step detection accuracy", "pal", "opal", "Sensewear Armband Mini", "step count", "activpal", "speed", "activity recognition protocol", "sensor", "Nike", "percentage", "ADPM", "Activity Recognition Accuracy", "task duration.The Movemonitor", "Tractivity", "inc", "Angular velocity signals", "step count detection accuracy", "Fuelband", "Physical Activity Monitors"], "article_id"=>1343426, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Fabio A. Storm", "Ben W. Heller", "Claudia Mazzà"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0118723.t005", "stats"=>{"downloads"=>2, "page_views"=>23, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Classification_of_the_performed_activities_for_the_ActivPAL_sensor_/1343426", "title"=>"Classification of the performed activities for the ActivPAL sensor.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-03-19 03:31:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/1961740"], "description"=>"<p>The solid lines indicate the mean step count difference between the OPAL sensor and each monitor. The dashed lines indicate mean ± Limits of Agreement (1.96*SD). Regression lines, relevant equations and Pearson’s correlation coefficients (r) are shown for the Nike+ Fuelband and the Sensewear Armband Mini.</p>", "links"=>[], "tags"=>["Step detection accuracy", "pal", "opal", "Sensewear Armband Mini", "step count", "activpal", "speed", "activity recognition protocol", "sensor", "Nike", "percentage", "ADPM", "Activity Recognition Accuracy", "task duration.The Movemonitor", "Tractivity", "inc", "Angular velocity signals", "step count detection accuracy", "Fuelband", "Physical Activity Monitors"], "article_id"=>1343421, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Fabio A. Storm", "Ben W. Heller", "Claudia Mazzà"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0118723.g004", "stats"=>{"downloads"=>3, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Bland_Altman_plots_for_step_count_for_a_the_Movemonitor_ActivPAL_and_One_and_b_for_the_Up_Tractivity_Nike_Fuelband_and_Sensewear_Armband_Mini_/1343421", "title"=>"Bland-Altman plots for step count for (a) the Movemonitor, ActivPAL and One, and (b) for the Up, Tractivity, Nike+ Fuelband and Sensewear Armband Mini.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-03-19 03:31:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/1961736"], "description"=>"<p>The figure shows the angular velocity signal as measured by one of the shank sensors in the sagittal plane during a portion of a randomly selected indoor walking trial. The shown portion of the signal includes walking, stopping and turning. The maxima detected by the algorithm used to detect single steps are also highlighted (dotted vertical lines).</p>", "links"=>[], "tags"=>["Step detection accuracy", "pal", "opal", "Sensewear Armband Mini", "step count", "activpal", "speed", "activity recognition protocol", "sensor", "Nike", "percentage", "ADPM", "Activity Recognition Accuracy", "task duration.The Movemonitor", "Tractivity", "inc", "Angular velocity signals", "step count detection accuracy", "Fuelband", "Physical Activity Monitors"], "article_id"=>1343417, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Fabio A. Storm", "Ben W. Heller", "Claudia Mazzà"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0118723.g002", "stats"=>{"downloads"=>0, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Typical_angular_velocity_signal_of_the_shank_in_the_sagittal_plane_during_consecutive_steps_/1343417", "title"=>"Typical angular velocity signal of the shank in the sagittal plane during consecutive steps.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-03-19 03:31:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/1961734"], "description"=>"<p>The figure shows the location of the sensors on a subject’s body: Movemonitor (1), Up (2), One (3), ActivPAL (4) Tractivity (5), Nike+ Fuelband (6), Sensewear Armband Mini (7), OPAL (8).</p>", "links"=>[], "tags"=>["Step detection accuracy", "pal", "opal", "Sensewear Armband Mini", "step count", "activpal", "speed", "activity recognition protocol", "sensor", "Nike", "percentage", "ADPM", "Activity Recognition Accuracy", "task duration.The Movemonitor", "Tractivity", "inc", "Angular velocity signals", "step count detection accuracy", "Fuelband", "Physical Activity Monitors"], "article_id"=>1343415, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Fabio A. Storm", "Ben W. Heller", "Claudia Mazzà"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0118723.g001", "stats"=>{"downloads"=>0, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sensor_placement_/1343415", "title"=>"Sensor placement.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-03-19 03:31:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/1961747", "https://ndownloader.figshare.com/files/1961748", "https://ndownloader.figshare.com/files/1961749"], "description"=>"<div><p>The aim of this study was to compare the seven following commercially available activity monitors in terms of step count detection accuracy: Movemonitor (Mc Roberts), Up (Jawbone), One (Fitbit), ActivPAL (PAL Technologies Ltd.), Nike+ Fuelband (Nike Inc.), Tractivity (Kineteks Corp.) and Sensewear Armband Mini (Bodymedia). Sixteen healthy adults consented to take part in the study. The experimental protocol included walking along an indoor straight walkway, descending and ascending 24 steps, free outdoor walking and free indoor walking. These tasks were repeated at three self-selected walking speeds. Angular velocity signals collected at both shanks using two wireless inertial measurement units (OPAL, ADPM Inc) were used as a reference for the step count, computed using previously validated algorithms. Step detection accuracy was assessed using the mean absolute percentage error computed for each sensor. The Movemonitor and the ActivPAL were also tested within a nine-minute activity recognition protocol, during which the participants performed a set of complex tasks. Posture classifications were obtained from the two monitors and expressed as a percentage of the total task duration.</p><p>The Movemonitor, One, ActivPAL, Nike+ Fuelband and Sensewear Armband Mini underestimated the number of steps in all the observed walking speeds, whereas the Tractivity significantly overestimated step count. The Movemonitor was the best performing sensor, with an error lower than 2% at all speeds and the smallest error obtained in the outdoor walking. The activity recognition protocol showed that the Movemonitor performed best in the walking recognition, but had difficulty in discriminating between standing and sitting. Results of this study can be used to inform choice of a monitor for specific applications.</p></div>", "links"=>[], "tags"=>["Step detection accuracy", "pal", "opal", "Sensewear Armband Mini", "step count", "activpal", "speed", "activity recognition protocol", "sensor", "Nike", "percentage", "ADPM", "Activity Recognition Accuracy", "task duration.The Movemonitor", "Tractivity", "inc", "Angular velocity signals", "step count detection accuracy", "Fuelband", "Physical Activity Monitors"], "article_id"=>1343428, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Fabio A. Storm", "Ben W. Heller", "Claudia Mazzà"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0118723.s001", "https://dx.doi.org/10.1371/journal.pone.0118723.s002", "https://dx.doi.org/10.1371/journal.pone.0118723.s003"], "stats"=>{"downloads"=>9, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Step_Detection_and_Activity_Recognition_Accuracy_of_Seven_Physical_Activity_Monitors_/1343428", "title"=>"Step Detection and Activity Recognition Accuracy of Seven Physical Activity Monitors", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2015-03-19 03:31:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/1961744"], "description"=>"<p>Summary of the activities performed during the activity recognition protocol.</p>", "links"=>[], "tags"=>["Step detection accuracy", "pal", "opal", "Sensewear Armband Mini", "step count", "activpal", "speed", "activity recognition protocol", "sensor", "Nike", "percentage", "ADPM", "Activity Recognition Accuracy", "task duration.The Movemonitor", "Tractivity", "inc", "Angular velocity signals", "step count detection accuracy", "Fuelband", "Physical Activity Monitors"], "article_id"=>1343425, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Fabio A. Storm", "Ben W. Heller", "Claudia Mazzà"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0118723.t004", "stats"=>{"downloads"=>3, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_of_the_activities_performed_during_the_activity_recognition_protocol_/1343425", "title"=>"Summary of the activities performed during the activity recognition protocol.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-03-19 03:31:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/1961742"], "description"=>"<p>Details of the monitors tested in this study.</p>", "links"=>[], "tags"=>["Step detection accuracy", "pal", "opal", "Sensewear Armband Mini", "step count", "activpal", "speed", "activity recognition protocol", "sensor", "Nike", "percentage", "ADPM", "Activity Recognition Accuracy", "task duration.The Movemonitor", "Tractivity", "inc", "Angular velocity signals", "step count detection accuracy", "Fuelband", "Physical Activity Monitors"], "article_id"=>1343423, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Fabio A. Storm", "Ben W. Heller", "Claudia Mazzà"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0118723.t002", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Details_of_the_monitors_tested_in_this_study_/1343423", "title"=>"Details of the monitors tested in this study.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-03-19 03:31:53"}

PMC Usage Stats | Further Information

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  • {"unique-ip"=>"46", "full-text"=>"37", "pdf"=>"16", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2020", "month"=>"2"}
  • {"unique-ip"=>"64", "full-text"=>"55", "pdf"=>"29", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2020", "month"=>"3"}
  • {"unique-ip"=>"37", "full-text"=>"42", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2020", "month"=>"4"}
  • {"unique-ip"=>"48", "full-text"=>"45", "pdf"=>"18", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"5"}
  • {"unique-ip"=>"35", "full-text"=>"31", "pdf"=>"15", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"6"}
  • {"unique-ip"=>"23", "full-text"=>"12", "pdf"=>"13", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"7"}
  • {"unique-ip"=>"19", "full-text"=>"17", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2020", "month"=>"8"}
  • {"unique-ip"=>"31", "full-text"=>"37", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"9"}
  • {"unique-ip"=>"18", "full-text"=>"23", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"10"}

Relative Metric

{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}
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