Studying Upper-Limb Kinematics Using Inertial Sensors Embedded in Mobile Phones

Background In recent years, there has been a great interest in analyzing upper-limb kinematics. Inertial measurement with mobile phones is a convenient and portable analysis method for studying humerus kinematics in terms of angular mobility and linear acceleration. Objective The aim of this analysis was to study upper-limb kinematics via mobile phones through six physical properties that correspond to angular mobility and acceleration in the three axes of space. Methods This cross-sectional study recruited healthy young adult subjects. Humerus kinematics was studied in 10 young adults with the iPhone4. They performed flexion and abduction analytical tasks. Mobility angle and lineal acceleration in each of its axes (yaw, pitch, and roll) were obtained with the iPhone4. This device was placed on the right half of the body of each subject, in the middle third of the humerus, slightly posterior. Descriptive statistics were calculated. Results Descriptive graphics of analytical tasks performed were obtained. The biggest range of motion was found in pitch angle, and the biggest acceleration was found in the y-axis in both analytical tasks. Focusing on tridimensional kinematics, bigger range of motion and acceleration was found in abduction (209.69 degrees and 23.31 degrees per second respectively). Also, very strong correlation was found between angular mobility and linear acceleration in abduction (r=.845) and flexion (r=.860). Conclusions The use of an iPhone for humerus tridimensional kinematics is feasible. This supports use of the mobile phone as a device to analyze upper-limb kinematics and to facilitate the evaluation of the patient.

[1]  T. Russell Telerehabilitation: a coming of age. , 2009, The Australian journal of physiotherapy.

[2]  M. Marfell-Jones,et al.  International standards for anthropometric assessment. , 2012 .

[3]  T. Russell,et al.  Implications of regulatory requirements for smartphones, gaming consoles and other devices. , 2011, Journal of physiotherapy.

[4]  Brian Coley,et al.  Objective evaluation of shoulder function using body-fixed sensors: a new way to detect early treatment failures? , 2011, Journal of shoulder and elbow surgery.

[5]  Antonio I Cuesta-Vargas,et al.  The use of inertial sensors system for human motion analysis , 2010, Physical therapy reviews : PTR.

[6]  Claudio Cobelli,et al.  Motion analysis of front crawl swimming applying CAST technique by means of automatic tracking , 2013, Journal of sports sciences.

[7]  Lex M Bouter,et al.  Interobserver reproducibility of the visual estimation of range of motion of the shoulder. , 2005, Archives of physical medicine and rehabilitation.

[8]  Susanne Fuchs-Winkelmann,et al.  Objective Assessment of shoulder mobility with a new 3D gyroscope - a validation study , 2011, BMC musculoskeletal disorders.

[9]  Stephanie Morton,et al.  Reliability and validity of goniometric iPhone applications for the assessment of active shoulder external rotation , 2014, Physiotherapy theory and practice.

[10]  Jung-Taek Hwang,et al.  How to assess scapular dyskinesis precisely: 3-dimensional wing computer tomography--a new diagnostic modality. , 2013, Journal of shoulder and elbow surgery.

[11]  Wai-Yin Wong,et al.  Trunk posture monitoring with inertial sensors , 2008, European Spine Journal.

[12]  Meinhard Sesselmann,et al.  Measurement of scapular kinematics with the moiré fringe projection technique. , 2010, Journal of biomechanics.

[13]  Joo Han Oh,et al.  Within-day reliability of shoulder range of motion measurement with a smartphone. , 2012, Manual therapy.

[14]  Josien C. van den Noort,et al.  Reliability and precision of 3D wireless measurement of scapular kinematics , 2014, Medical & Biological Engineering & Computing.

[15]  S. Azen,et al.  Reliability of goniometric measurements. , 1978, Physical therapy.

[16]  M. Kolber,et al.  The reliability and minimal detectable change of shoulder mobility measurements using a digital inclinometer , 2011, Physiotherapy theory and practice.

[17]  Giorgio Ferriero,et al.  Mobile smartphone applications for body position measurement in rehabilitation: a review of goniometric tools. , 2014, PM & R : the journal of injury, function, and rehabilitation.

[18]  Richard Walter,et al.  Inter- and intra-observer reliability of a smartphone application for measuring hallux valgus angles. , 2013, Foot and ankle surgery : official journal of the European Society of Foot and Ankle Surgeons.

[19]  Morey J Kolber,et al.  The reliability and concurrent validity of shoulder mobility measurements using a digital inclinometer and goniometer: a technical report. , 2012, International journal of sports physical therapy.

[20]  Maxime Raison,et al.  Coupling between 3D displacements and rotations at the glenohumeral joint during dynamic tasks in healthy participants. , 2014, Clinical biomechanics.

[21]  Andrea Giovanni Cutti,et al.  Shoulder biomechanics and the success of translational research , 2014, Medical & Biological Engineering & Computing.

[22]  D. Theodoros,et al.  Telerehabilitation: current perspectives. , 2008, Studies in health technology and informatics.

[23]  Kamiar Aminian,et al.  iShould: functional evaluation of the shoulder using a Smartphone , 2012 .

[24]  Trevor Russell Goniometry via the internet. , 2007, The Australian journal of physiotherapy.

[25]  Wai Yin Wong,et al.  Clinical Applications of Sensors for Human Posture and Movement Analysis: A Review , 2007, Prosthetics and orthotics international.

[26]  Andrea Giovanni Cutti,et al.  Intra-protocol repeatability and inter-protocol agreement for the analysis of scapulo-humeral coordination , 2013, Medical & Biological Engineering & Computing.

[27]  Antonio I. Cuesta-Vargas,et al.  Differences in Trunk Kinematic between Frail and Nonfrail Elderly Persons during Turn Transition Based on a Smartphone Inertial Sensor , 2013, BioMed research international.

[28]  T. Russell,et al.  Assessment and Diagnosis of Musculoskeletal Shoulder Disorders over the Internet , 2012, International journal of telemedicine and applications.

[29]  Stepán Obdrzálek,et al.  Upper Extremity Reachable Workspace Evaluation with Kinect , 2013, MMVR.

[30]  Joseph M Hart,et al.  Validation of an innovative method of shoulder range-of-motion measurement using a smartphone clinometer application. , 2014, Journal of shoulder and elbow surgery.

[31]  Lauren Beaupre,et al.  Evaluating change in clinical status: reliability and measures of agreement for the assessment of glenohumeral range of motion. , 2010, North American journal of sports physical therapy : NAJSPT.

[32]  M. Begon,et al.  Elucidating the scapulo-humeral rhythm calculation: 3D joint contribution method , 2015, Computer methods in biomechanics and biomedical engineering.

[33]  Yoon Sang Kim,et al.  Mobile Assessment System for Shoulder Joint Rehabilitation: System Development and Preliminary Study , 2014, BSBT 2014.

[34]  Laura Rocchi,et al.  Ambulatory measurement of shoulder and elbow kinematics through inertial and magnetic sensors , 2008, Medical & Biological Engineering & Computing.

[35]  Peter J Millett,et al.  Effect of plane of arm elevation on glenohumeral kinematics: a normative biplane fluoroscopy study. , 2013, The Journal of bone and joint surgery. American volume.

[36]  B Grimm,et al.  Inertia based functional scoring of the shoulder in clinical practice. , 2014, Physiological measurement.

[37]  G. Verni,et al.  Ambulatory measurement of the scapulohumeral rhythm: intra- and inter-operator agreement of a protocol based on inertial and magnetic sensors. , 2012, Gait & posture.

[38]  Francesco Sartorio,et al.  Reliability of a New Application for Smartphones (DrGoniometer) for Elbow Angle Measurement , 2011, PM & R : the journal of injury, function, and rehabilitation.

[39]  Peter J Millett,et al.  The effects of arm elevation on the 3-dimensional acromiohumeral distance: a biplane fluoroscopy study with normative data. , 2012, Journal of shoulder and elbow surgery.

[40]  G R Johnson,et al.  A framework for the definition of standardized protocols for measuring upper-extremity kinematics. , 2009, Clinical biomechanics.

[41]  Richard W. Bohannon,et al.  Clinical measurement of range of motion. Review of goniometry emphasizing reliability and validity. , 1987, Physical therapy.

[42]  Edward G. McFarland,et al.  Examination of the Shoulder: The Complete Guide , 2006 .

[43]  Susanne Fuchs-Winkelmann,et al.  Objective assessment, repeatability, and agreement of shoulder ROM with a 3D gyroscope , 2013, BMC Musculoskeletal Disorders.

[44]  Sameer Nagda,et al.  Defining functional shoulder range of motion for activities of daily living. , 2012, Journal of shoulder and elbow surgery.