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Activity Sensor

The best tool for measuring physical activity in everyday life!




Move 4 - Activity Sensor


Sensor getragen am Handgelenk

It has never been so easy to capture movement data quickly and precisely in everyday life!


The Move 4 combines excellent signal acquisition with unsurpassed convenience, a benefit for both participants and researchers alike. Begin your study assured in the quality of your data's fitness for publication.

High precision

Obtain precise data from our advanced device platform, capturing a multitude of signals at research level quality. Benefit from our tested and validated algorithms or conduct your own analysis from the raw data.


Whatever your approach, our sensors make data acquisition in every-day life easy and efficient. All the data you need, from when you need it.

Everyday life and real time

Analyse your participants in their every-day life with extensive measurement durations.


In addition, movisens offers the unique option of sensor coupling for all our sensors. Whilst recording the participants physiology, our sensors analyze physiological parameters and transmit the results via Bluetooth to a smartphone equipped with movisensXS. Algorithms within movisensXS process this data and can trigger a questionnaire for the participant when the set conditions occur. If you want to investigate physiological changes such as a high level of activity or sedentary behavior, such events can act as triggers for queries within the study.

Multimodal data analysis

Combine your activity data with experience sampling data.


The Move 4 offers researchers superior flexibility as our analysis algorithms extract accurate activity parameters from a variety of wearing positions. This allows you to find the most convenient solution for your participants and your study. To get the most out of the raw data captured by the sensor, most researchers prefer to analyze it using the movisens DataAnalyzer's, AI-based, validated algorithms.

Move 4
https://www.movisens.com/en/products/activity-sensor/
Apply for free student project
Documentation of the Move 4

Benefit from our many years of experience in the field of ambulatory assessment and let us put together the right analysis solution for you

Software_DataAnalyzer

DataAnalyzer

Modular software for sensor data analysis and report generation

Smartphone mit movisensXS

movisensXS

The most comprehensive mobile research platform for Experience Sampling

Software DataMerger
DataMerger

Tool for the integration of data assessed with different methods

Our Move 4 is used in the following areas




running person

Activity Monitoring

  • Measurement of steps, activity classes, movement intensity and/or activity level
  • Energy Expenditure estimation in everyday life
  • Joint recording of objective and subjective aspects of physical activity

  • Recommendations for activity monitoring

Sedentary Behaviour

  • Acquisition of inactivity
  • Distinction between sitting/lying & standing
  • Capture sedentary behavioral changes and the intensity of physical activity

  • Recommendations for sedentary behaviour



sitting woman



hängematte

Sleep Monitoring

  • Sleep Detection
  • Subjective sleep analysis

  • Recommendations for Sleep Monitoring

Interactive Ambulatory Assessment

  • Investigating phases of physical activity and inactivity
  • Combining different sensor parameters
  • Trigger algorithms

  • Recommendations for IAA



young scientists



Cover sedentary mood study

Blog - SedentaryMood-Study

    What influence does Sedentary Behavior have on mood?

    The implementation of the study, the course of the study, the measurement methods as well as the measurement recommendations and findings will be presented and described here at regular intervals. The individual articles in the study diary are intended to build on each other to describe the overall course of the study.

    Read more in our Sedentary Mood study articles

Look and Feel - Sensor triggered interactive ambulatory assessment

Matching products and services

ECGMove 4
EcgMove 4

Sensor for the acquisition of ECG- and activity data

EdaMove 4 worn
EdaMove 4

Sensor for the acquisition of electrodermal activity and activity data


Accessories and Consumables

Accessories and Consumables for the movisens sensors

Schulungs-Icon
Consulting

Consulting and Training regarding technologies and methods for ambulatory assessment and mobile monitoring

Customizing-Icon
Customizing

Adaption and extension of movisens products to your requirements

Workshops-Icon
Webinars

We offer webinars on themes related to ambulatory assessment, physiological parameters, and experience sampling

Useful Information

Raw data and live data

Raw data

Also known as primary data, this is obtained directly during an observation, measurement or data collection and remains unprocessed. It represents the original information recorded by sensors. Raw data from acceleration, ECG, and EDA are usually displayed as graphs. Calculating output parameters such as HR, steps, and energy expenditure from these raw signals requires algorithms fit for purpose.
Advantage:
Raw data allows long term storage and the implementation of new analysis methods, e.g. for a new algorithm, new AI and it can also be fed into other software.
Disadvantage:
They contain a large amount of data and require more storage space.

Live data

In addition to offline calculation, the Move 4 allows the live analysis of physical activity parameters in conjunction with movisensXS. In live mode, Movement Acceleration, Step Count, and Body Position can be measured, calculated and transmitted via the Bluetooth Smart interface at the rate of 1 value per minute.

Technical Data

Power supply

Lithium-Polymer-Battery

Battery voltage

3,7 V

Number of charging cycles

300 (with 1 C / 1 C > 80%)

Internal memory

4 GB

Maximum recording capacity

4 weeks

Battery run time

~ 7 days

Recharging time

~ 1 hour

Size of sensor (W x H x D)

62,3 mm x 38,6 mm x 11,5 mm

Weight of sensor

25 g

Protection rate

Waterproof (IP64)

Internal sensors

3D acceleration sensor:

Measurement range: +/- 16 g

Output rate: 64 Hz

 

Rotation rate sensor:

Measurement range: +/-2000dps

Resolution: 70 mdps

Output rate: 64 Hz

 

Pressure sensor:

Measurement range: 300 - 1100 hPa

Noise: 0,03 hPa

Output rate: 8 Hz

 

Temperature sensor:

Output rate: 1 Hz

Live analysis

Movement Acceleration

Step count

Indicators

LED, 3-color

Vibration alarm

User Interfaces

Marker (tapping)

Interfaces

Micro-USB, Bluetooth Smart (4.0)

API

Java API for USB (Windows)

Example for Bluetooth Smart (Android)

Wear locations

Hip, Chest, Wrist, Upper Arm, Ankle, Thigh

Wearing systems

Wrist Band, Belt Adapter and Belt

Environmental conditions

Temperature:

-20 °C to 60 °C

0 °C to 45 °C during charging

Atmospheric pressure:

300 to 1200 hPa absolute

Warranty

2 years

Literature and Validation

  • Influence of motivational interviewing on postoperative mobilization in the enhanced recovery after surgery (ERAS®) pathway in elective colorectal surgery - a randomized patient-blinded pilot study.
    R. Wiesenberger & J. Müller & M. Kaufmann et al. (2024) in: Langenbecks Arch Surg (409). Read more...
  • Impact of a Semi-Rigid Knee Orthotic Intervention on Pain, Physical Activity, and Functional Capacity in Patients with Medial Knee Osteoarthritis.
    B. J. Stetter & J. Fiedler & M. Arndt et al. (2024) in: Journal of Clinical Medicine (13 (6)). Read more...
  • Psychomotor Slowing in Psychosis and Inhibitory Repetitive Transcranial Magnetic Stimulation.
    S. Walther & D. Alexaki & F. Weiss et al. (2024) in: JAMA Psychiatry. Read more...
  • Exploring the Link between Lifestyle, Inflammation, and Insulin Resistance through an Improved Healthy Living Index.
    F. Bruckner & J.R. Gruber & A. Ruf et al. (2024) in: MDPI (16(3)). Read more...
  • Development of a Machine Learning Model to Detect Freezing of Gait in Parkinson Patients.
    K.Y. Hilbrants (2024). Read more...
  • Determination of cut-off points for the Move4 accelerometer in children aged 8–13 years.
    F. Beck & I. Marzi & A. Eisenreich et al. (2023) in: BMC Sports Science, Medicine and Rehabilitation (15, 163). Read more...
  • Momentary within-subject associations of affective states and physical behavior are moderated by weather conditions in real life: an ambulatory assessment study.
    I. Timm & M. Reichert & U. Ebner-Priemer et al. (2023) in: International Journal of Behavioral Nutrition and Physical Activity (20). Read more...
  • Microtemporal Dynamics of Dietary Intake, Physical Activity, and Impulsivity in Adult Attention-Deficit/Hyperactivity Disorder: Ecological Momentary Assessment Study Within Nutritional Psychiatry.
    A. Ruf & A. B. Neubauer & E. D. Koch et al. (2023) in: JMIR Publications (10). Read more...
  • Ecological Momentary Assessment in Nutritional Psychiatry: Microtemporal Dynamics of Dietary Intake, Physical Activity, and Impulsivity in Adult ADHD.
    A. Ruf & A. B. Neubauer & E. D. Koch et al. (2023) in: JMIR Mental Health. Read more...
  • Momentary associations between sedentary bouts, cognitive load and mood in daily life: An ambulatory assessment study.
    M. Giurgio & U. Ebner-Priemer (2023) in: Mental Health and Physical Activity (25). Read more...
  • The Work Lifestyle-integrated Functional Exercise Program for Preventing Functional Decline in Employees over 55 years: Development and Initial Evaluation.
    Y. Ritter & D. Pfister & G.M. Steckhan et al. (2023). Read more...
  • Multicentre, interventional, single-arm study protocol of telemonitored circadian rhythms and patient-reported outcomes for improving mFOLFIRINOX safety in patients with pancreatic cancer.
    M. Bouchahda & A. Ulusakarya & A. Thirot-Bidault et al. (2023) in: BMJ Open (13(6)). Read more...
  • Microstructural white matter biomarkers of symptom severity and therapy outcome in catatonia: Rationale, study design and preliminary clinical data of the whiteCAT study.
    D. Hirjak & G.A. Brandt & R. Peretzke et al. (2023) in: Schizophrenia Research. Read more...
  • Combined physical activity training versus aerobic activity training in unipolar depressive disorder: a quasi-randomised evaluation study.
    A. Berwinkel & M. Driessen & T. Beblo et al. (2023) in: Neuropsychiatr. Read more...
  • At Crossroads in a Virtual City: Effect of Spatial Disorientation on Gait Variability and Psychophysiological Response among Healthy Older Adults.
    C. O. Amaefule & S. Lüdtke & A. Klostermann et al. (2022) in: Gerontology. Read more...
  • The 8th International Conference on Ambulatory Monitoring of Physical Activity and Movement: Active and Sitting Time Precursors to Mood in Young Adults.
    B. Clark & E. Winkler & M. Giurgio et al. (2022) in: Journal for the Measurement of Physical Behaviour (5; 4). Read more...
  • Effects of strength exercise interventions on activities of daily living, motor performance, and physical activity in children and adolescents with leukemia or non-Hodgkin lymphoma: Results from the randomized controlled ActiveADL Study.
    D. Gaser & C. Peters & R. Oberhoffer-Fritz et al. (2022) in: Frontiers in Pediatrics. Read more...
  • Effectiveness of an evidence-based care pathway to improve mobility and participation in older patients with vertigo and balance disorders in primary care (MobilE-PHY2): Study protocol for a multicentre cluster-randomised controlled trial.
    C. Horstmannshoff & S. Skudlik & J. Petermann et al. (2022) in: Research Square. Read more...
  • The Behavioral Mapping of Psychomotor Slowing in Psychosis Demonstrates Heterogeneity Among Patients Suggesting Distinct Pathobiology.
    N. Nadesalingam & S. Lefebvre & D. Alexaki et al. (2022). Read more...
  • Measuring catatonia motor behavior with objective instrumentation.
    S. von Känel & N. Nadesalingam & D. Alexaki et al. (2022) in: Frontiers in Psychology. Read more...
  • Mood-enhancing Physical Activity in Individuals with Attention-Deficit/Hyperactivity Disorder (ADHD) and Healthy Youths – Daily Life Investigations by Ambulatory Assessment.
    E.D. Koch (2022). Read more...
  • A temporal classification method based on behavior time series data in patients with behavioral variant of frontotemporal dementia and apathy.
    C. Peltier & F. Lejeune & L.G.T. Jorgensen et al. (2022) in: Journal of Neuroscience Methods (376). Read more...
  • The association of stress and physical activity: Mind the ecological fallacy.
    M. Reichert & S. Brüßler & I. Reinhardt et al. (2022) in: German Journal of Exercise and Sport Research (52). Read more...
  • Influence of Sit-Stand Tables in Classrooms on Children’s Sedentary Behavior and Teacher’s Acceptance and Feasibility: A Mixed-Methods Study.
    P. Schwenke & M. Coenen (2022) in: Environmental Research and Public Health (19 (11)). Read more...
  • Sleep quality, valence, energetic arousal, and calmness as predictors of device-based measured physical activity during a three-week mHealth intervention.
    J. Fiedler & C. Seiferth & T. Eckert et al. (2022) in: German Journal of Exercise and Sport Research. Read more...
  • Equivalency of four research-grade movement sensors to assess movement behaviors and its implications for population surveillance.
    J.H. Migueles & P. Molina-Garcia & L.V. Torrez-Lopez et al. (2022) in: Scientific Reports (12). Read more...
  • Analysis of self-reported activities of daily living, motor performance and physical activity among children and adolescents with cancer: Baseline data from a randomised controlled trial assessed shortly after diagnosis of leukaemia or non-Hodgkin lymphoma.
    D. Gaser & C. Peters & M. Götte et al. (2022) in: Wiley. Read more...
  • Functional connectivity correlates of reduced goal-directed behaviorsin behavioural variant frontotemporal dementia.
    V. Godefroy & B. Batrancourt & S. Charron et al. (2022) in: Research Square. Read more...
  • Actigraph-Measured Movement Correlates of Attention-Deficit/Hyperactivity Disorder (ADHD) Symptoms in Young People with Tuberous Sclerosis Complex (TSC) with and without Intellectual Disability and Autism Spectrum Disorder (ASD).
    T. Earnest & E. Shephard & C. Tye et al. (2020) in: Brain Sciences (8). Read more...
  • Accuracy of Sedentary Behavior–Triggered Ecological Momentary Assessment for Collecting Contextual Information: Development and Feasibility Study.
    M. Giurgiu & C. Niermann & U. Ebner-Priemer et al. (2020) in: JMIR mHealth and uHealth (8).
  • Mood and dysfunctional cognitions constitute within - subject antecedents and consequences of exercise in eating disorders.
    M. Reichert & S. Schlegel & F. Jagan et al. (2020) in: Psychotherapy and Psychosomatics (89).
  • OREBA: A Dataset for Objectively Recognizing Eating Behaviour and Associated Intake.
    P.-V. Rouast & H. Heydarian & M.-T.-P. Adam et al. (2020).
  • Improving mobility and participation of older people with vertigo, dizziness and balance disorders in primary care using a care pathway: feasibility study and process evaluation.
    E. Seckler & V. Regauer & M. Krüger et al. (2020) in: Research Square.
  • Fear of Physical Activity, Anxiety, and Depression. Barriers to Physical Activity in Outpatients With Heart Failure?.
    H. Spaderna & J. M. Hoffmann & S. Hellwig et al. (2020) in: European Journal of Health Psychology (27). Read more...
  • The Freiburg sport therapy program for eating disorders: a randomized controlled trial.
    A Zeeck & S. Schlegel & F. Jagan et al. (2020) in: Journal of Eating Disorders (8). Read more...
  • A neural mechanism for affective well-being: Subgenual
    cingulate cortex mediates real-life effects
    of nonexercise activity on energy.
    R. Markus & U. Braun & G. Gan et al. (2020) in: Science advances (6).
  • Development of a classification system for assessing apathy’s degree in patients with behavioral variant of frontotemporal dementia.
    P. Fulcher (2020) in: MASTER’S DEGREE THESIS.
  • Validating Accelerometers for the Assessment of Body Position and Sedentary Behavior.
    M. Giurgiu & J.B.J. Bussmann & H. Hill et al. (2020) in: Journal for the Measurement of Physical Behaviour (Volume 3: Issue 3). Read more...
  • Breaking Up Sedentary Behavior Optimally to Enhance Mood.
    M. Giurgio & E.D. Koch & R.C. Plotnikoff et al. (2020) in: Medicine & Science in Sports & Exercise (52).
  • Real-Time Detection of Spatial Disorientation in Persons with Mild Cognitive Impairment and Dementia.
    J. Schaat & P. Koldrack & K. Yordanova et al. (2019) in: Gerontology (1).
  • Dynamics of Intraindividual Variability in Everyday Life Affect Across
    Adulthood and Old Age.
    M. Katana (2019).
  • Embodied learning in the classroom: Effects on primary school children's attention and foreign language vocabulary learning.
    M. Schmidt & V. Benzig & A. R. Wallman-Jones et al. (2019) in: Psychology of Sport and Exercise (43). Read more...
  • Neural correlates of individual differences in affective benefit of real-life urban green space exposure.
    Heike Tost & Markus Reichert & Urs Braun et al. (2019) in: Nature Neuroscience (7). Read more...
  • Using Acceleration Data for Detecting Temporary Cognitive Overload in Health Care Exemplified Shown in a Pill Sorting Task.
    L. Kohout & M. Butz & W. Stork (2019) in: 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS).
  • Sedentary behavior in everyday life relates negatively to mood: An ambulatory Assessment study.
    Marco Giurgiu & Elena D. Koch & Jörg Ottenbacher et al. (2019) in: Scandinavian Journal of Medicine & Science in Sports (29). Read more...
  • Promotion of physical activity-related health competence in physical education: study protocol for the GEKOS cluster randomized controlled trial.
    Stephanie Haible & Carmen Volk & Yolanda Demetriou et al. (2019) in: BMC Public Health (19). Read more...
  • Energy Expenditure During Incline Walking – Benefits of Integrating a Barometer into Activity Monitors.
    M. Armbruster & P. Anastasopoulou & S. Altmann et al. (2018) in: American Journal of Sports Science (6). Read more...
  • Individual Differences in the Competence for Physical-Activity-Related Affect Regulation Moderate the Activity–Affect Association in Real-Life Situations.
    Gorden Sudeck & Stephanie Jeckel & Tanja Schubert (2018) in: Journal of Sport and Exercise Psychology (40). Read more...
  • Intermittent Fasting (Alternate Day Fasting) in Healthy, Non-obese Adults: Protocol for a Cohort Trial with an Embedded Randomized Controlled Pilot Trial.
    Norbert J. Tripolt & Slaven Stekovic & Felix Aberer et al. (2018) in: Advances in Therapy (35). Read more...
  • Bright light therapy versus physical exercise to prevent co-morbid depression and obesity in adolescents and young adults with attention-deficit / hyperactivity disorder: study protocol for a randomized controlled trial.
    Jutta S. Mayer & Katharina Hees & Juliane Medda et al. (2018) in: Trials (19). Read more...
  • A novel algorithm for detecting human circadian rhythms using a thoracic temperature sensor Article history :.
    Aly Chkeir & Farah Mourad-chehade & Jacques Beau et al. (2017) in: Advances in Science, Technology and Engineering Systems Journal (2). Read more...
  • Physical Activity and Depressive Mood in the Daily Life of Older Adults.
    Andrea E. Gruenenfelder-Steiger & Marko Katana & Annika A. Martin et al. (2017) in: GeroPsych (30). Read more...
  • Measuring Fear of Physical Activity in Patients with Heart Failure.
    Jeremia M. Hoffmann & Susan Hellwig & Vincent M. Brandenburg et al. (2017) in: International Journal of Behavioral Medicine (25). Read more...
  • Lightweight Visual Data Analysis on Mobile Devices - Providing Self-Monitoring Feedback.
    Simon Butscher & Yunlong Wang (2016) in: VVH 2016 - 1st International Workshop on "Valuable visualization of healthcare information": from the quantified self data to conversations (in conjunction with AVI '16). Read more...
  • Contributions à l’élaboration d’un système d’aide médico-sociale à l’aide d’un robot humanoïde.
    Louise Devigne (2015). Read more...
  • Situationsadaptive Navigationsassistenz für Menschen mit Demenz.
    P. Koldrack & R. Henkel & K. Zarm et al. (2015) in: AAL-Kongress 2015. Read more...
  • Real-Time Management of Multimodal Streaming Data for Monitoring of Epileptic Patients.
    Dimitrios Triantafyllopoulos & Panagiotis Korvesis & Iosif Mporas et al. (2015) in: Journal of Medical Systems (40). Read more...
  • Bewegungsangst bei chronischer Herzinsuffizienz – Erste Ergebnisse zur Validierung eines Messinstruments.
    H. Spaderna & S. Hellwig & D. Hennig et al. (2015) in: 12. Kongress der Fachgrupppe Gesundheitspsychologie - Abstracts. Read more...
  • Fitness, kognitive Leistungsfähigkeit und Wohlbefinden bei jungen Erwachsenen - Interventionsstudien zum Einfluss von Ausdauertraining.
    Katrin Walter (2015). Read more...
  • Validation and comparison of two methods to assess human energy expenditure during free-living activities.
    P. Anastasopoulou & M. Tubic & S. Schmidt et al. (2014) in: PLOS (PLoS ONE 9(2): e90606). Read more...
  • Erfassung körperlicher Aktivität mittels Akzelerometrie - Möglichkeiten und Grenzen aus technischer Sicht.
    Stefan Hey & Panagiota Anastasopoulou & Birte von Haaren (2014) in: Bewegungstherapie und Gesundheitssport (30(02)). Read more...
  • Home-based system for physical activity monitoring in patients with multiple sclerosis (Pilot study).
    L. Shammas & T. Zentek & B. von Haaren et al. (2014) in: Biomedical engineering online (13). Read more...
  • Detection of Parameters to Quantify Neurobehavioral Alteration in Multiple Sclerosis Based on Daily Life Physical Activity and Gait Using Ambulatory Assessment.
    Layal Shammas & Birte von Haaren & Angela Kunzler et al. (2014) in: Zeitschrift für Neuropsychologie (25). Read more...
  • Using Support Vector Regression for Assessing Human Energy Expenditure Using a Triaxial Accelerometer and a Barometer.
    Panagiota Anastasopoulou & Sascha Härtel & Mirnes Tubic et al. (2013) in: Wireless Mobile Communication and Healthcare.
  • A Comparison of Two Commercial Activity Monitors for Measuring Step Counts During Different Everyday Life Walking Activities.
    P. Anastasopoulou & S. Härtel & S. Hey (2013) in: International Journal of Sports Science and Engineering (Vol. 07 (2013) No. 01). Read more...
  • The Association between Short Periods of Everyday Life Activities and Affective States: A Replication Study Using Ambulatory Assessment.
    Thomas Bossmann & Martina Kanning & Susanne Koudela-Hamila et al. (2013) in: Frontiers in Psychology (4). Read more...
  • Characteristics of the activity-affect association in inactive people: an ambulatory assessment study in daily life.
    B. von Haaren & S.N. Loeffler & S. Haertel et al. (2013) in: Frontiers in Movement Science and Sport Psychology (4).
  • Acute and medium term effects of a 10-week running intervention on mood state in apprentices.
    Katrin Walter & Birte von Haaren & Simone Löffler et al. (2013) in: Frontiers in Movement Science and Sport Psychology (4). Read more...
  • Measurement of daily mobility under fampridine-therapy with Movisens-system in patients with multiple sclerosis.
    R. Kempcke & T. Schultheiß & S. Sobek et al. (2012) in: 28th European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS).
  • Kindergarten in Bewegung. Zur Qualität von Bewegungskindergärten.
    R. Schwarz (2012) in: Kita aktuell.
  • Assessment der Mobilität im Alltag zur Unterstützung von MS-Patienten.
    Shammas, L. & Bachis, S. & Anastasopoulou, P. et al. (2012) in: 15. Jahrestagung der dvs-Kommission Gesundheit, Leipzig.
  • Assessment of Human Gait Speed and Energy Expenditure Using a Single Triaxial Accelerometer.
    Panagiota Anstasopoulou & Shammas Layal & Stefan Hey (2012) in: Wearable and Implantable Body Sensor Networks (BSN), 2012 Ninth International Conference on. Read more...
  • Aktuelle Messverfahren zur objektiven Erfassung körperlicher Aktivitäten unter besonderer Berücksichtigung der Schrittzahlmessung.
    D. Rosenbaum (2012) in: Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz (55). Read more...
  • A new method to estimate energy expenditure using accelerometry and barometry-based energy models.
    P Anastasopoulou & L. Shammas & J. Stumpp et al. (2011) in: 45. DGBMT Jahrestagung. Freiburg.
  • Validity of the kmsMove-sensor in calculating energy expenditure during different walking intensities.
    B. von Haaren & J.-P. Gnam & S. Helmholdt et al. (2011).
  • Estimation of energy expenditure using accelerometers and activity-based energy models - validation of a new device.
    S. Härtel & J. P Gnam & S. Löffler et al. (2011) in: European Review of Aging and Physical Activity (Volume 8). Read more...
  • Trends und Möglichkeiten zur Erfassung körperlicher Aktivität im Alltag.
    S. Hey & U. Großmann & J. Ottenbacher et al. (2011) in: Kinder bewegen - wissenschaftliche Energien bündeln. Jahrestagung der dvs-Kommission Gesundheit, Karlsruhe.
  • Bewegungskindergärten: empirische Befunde und praktisches Wissen.
    R. Schwarz (2011) in: S. Baadte, K. Bös, S. Scharenberg, R. Stark, A. Woll (Hrsg.), Kinder bewegen - Energien nutzen (S. 65-75). Landau: VEP..
  • Energieumsatzmessung mit Aktivitätssensoren – Validität des kmsMove-Akzelerometers.
    B. von Haaren & J.-P. Gnam & S. Härtel et al. (2011) in: Kinder bewegen - wissenschaftliche Energien bündeln.
  • Einsatz sensorgestützter Verfahren im Gesundheitswesen: Herausforderungen und Lösungsansätze.
    D.I.D.S. Saboor & M.F.H.M. Schallhart (2011). Read more...

All publications can be find here.

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