Portable Sensors Add Reliable Kinematic Measures to the Assessment of Upper Extremity Function
<p>The picture shows sensor placement on one arm and on the xiphoid process.</p> "> Figure 2
<p>Examples of a subject’s movement pattern during the finger-to-nose and drinking tasks for one rater. The patterns are illustrated using a normalized time window that was defined by the beginning and end of each repetition, giving 10 movement curves for each test. The illustration from the drinking task is collected from the test where the glass was placed 30 cm in front of the subject. The abbreviations are F (flexion; positive angles), E (extension; negative angles), Ab (abduction; positive angles), Ad (adduction; negative angles), R in (pronation(elbow); inward humeral rotation (shoulder); positive angles) and R out (supination (elbow); outward humeral rotation (shoulder); negative angles).</p> "> Figure 3
<p>Bland–Altman analysis of the inertial and optical sensor systems. The data from one subject in one session of 10 repetitions. (<b>a</b>) finger-to-nose and (<b>b</b>) drinking task.</p> "> Figure 4
<p>Illustration of inter-rater reliability between the two raters for the outcome measures of the (<b>a</b>) finger-to-nose and (<b>b</b>) drinking task. The regression lines are estimated using QR decomposition. Data of all 10 repetitions and 20 subjects are plotted.</p> "> Figure 5
<p>Bland–Altman analysis of the two raters for all outcome measures in the (<b>a</b>) finger-to-nose and (<b>b</b>) drinking task. Data of all 10 repetitions and 20 subjects are plotted.</p> "> Figure 6
<p>Illustrates the overall reliability (i.e., G-coefficient) estimated with a different number of repetitions for the finger-to-nose and drinking tasks based on one single rater. The results are subdivided into dominant arm (<b>left</b>) and non-dominant arm (<b>right</b>) for the different outcome measures. The dotted line marks the level for acceptable reliability, G = 0.7.</p> "> Figure A1
<p>Illustrates the overall reliability (i.e., G-coefficient) at different distance to the glass, with different number of repetitions (assuming there is only one rater present) for the drinking task, with data from one rater. The results are subdivided into dominant arm (<b>left</b>) and non-dominant arm (<b>right</b>) for the different outcome measures. The dotted line marks the level for acceptable reliability; G = 0.7.</p> ">
Abstract
:1. Introduction
2. Materials and Methods
2.1. Participants
2.2. Measurements
2.3. Study Design and Test Protocols
2.4. Data Processing
2.5. Statistics
3. Results
3.1. System Validity
3.2. Inter-Rater and Within-Subject Reliability
4. Discussion
4.1. Within-Subject Reliability
4.2. Rater Dependency
4.3. Proposed Protocol Design for Increased Reliability
4.4. Kinematic Assessment of the Finger-To-Nose Task
4.5. Kinematic Assessment of the Drinking Task
4.6. Methodological Considerations and Strengths
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
Side | Reliability | Cycle Time | Elbow FE | Elbow R | Shoulder FE | Shoulder AbAd | Shoulder R | |
---|---|---|---|---|---|---|---|---|
Dominant | Within-subject | 0.88 | 0.97 | 0.93 | 0.93 | 0.82 | 0.88 | |
Inter-rater | 0.72 | 0.46 | 0.15 | 0.73 | 0.81 | 0.74 | ||
G-coefficients | Overall | 0.88 | 0.64 | 0.26 | 0.87 | 0.90 | 0.89 | |
Non-dominant | Within-subject | 0.88 | 0.97 | 0.93 | 0.90 | 0.88 | 0.86 | |
Inter-rater | 0.75 | 0.49 | 0.25 | 0.50 | 0.59 | 0.67 | ||
Overall | 0.90 | 0.67 | 0.40 | 0.69 | 0.77 | 0.86 | ||
Dominant | Intercept | 5.11 *** | 56.22 *** | −12.61 * | 29.97 *** | −8.33 *** | 12.15 *** | |
(0.18) | (4.80) | (4.96) | (2.72) | (1.98) | (2.45) | |||
n = 399 | σ2rat | 0.00 | 20.72 | 0.00 | 3.32 | 0.00 | 2.33 | |
σ2rep | 0.01 | 0.97 | 0.48 | 0.00 | 7.53 | 0.36 | ||
σ2subj | 0.58 | 167.39 | 128.74 | 101.04 | 57.90 | 86.98 | ||
Model and | σ2rep_rat | 0.00 | 0.00 | 0.00 | 0.41 | 0.00 | 0.00 | |
variance | σ2subj_rat | 0.15 | 166.03 | 717.93 | 25.69 | 9.82 | 17.05 | |
components | σ2subj_rep | 0.01 | 1.55 | 4.79 | 1.19 | 1.22 | 2.13 | |
σ2residual | 0.08 | 10.10 | 60.34 | 8.84 | 5.92 | 12.41 | ||
Non-dominant | Intercept | 5.11 *** | 60.41 *** | −13.04 ** | 29.66 *** | −4.29 * | 15.13 *** | |
n = 377 | (0.17) | (4.53) | (4.40) | (2.53) | (2.17) | (1.99) | ||
σ2rat | 0.00 | 17.59 | 0.00 | 2.75 | 1.59 | 0.00 | ||
σ2rep | 0.01 | 0.31 | 1.51 | 0.00 | 0.51 | 0.00 | ||
σ2subj | 0.51 | 154.37 | 146.22 | 67.17 | 56.97 | 64.87 | ||
σ2rep_rat | 0.00 | 0.00 | 0.32 | 0.26 | 0.10 | 0.00 | ||
σ2subj_rat | 0.10 | 134.95 | 433.00 | 54.84 | 30.80 | 19.13 | ||
σ2subj_rep | 0.00 | 1.45 | 8.57 | 1.65 | 2.91 | 0.68 | ||
σ2residual | 0.07 | 8.45 | 32.93 | 11.19 | 9.16 | 13.18 |
Side | Reliability | Cycle Time | Elbow FE | Elbow R | Shoulder FE | Shoulder AbAd | Shoulder R | |
---|---|---|---|---|---|---|---|---|
Dominant | Within-subject | 0.91 | 0.87 | 0.98 | 0.86 | 0.91 | 0.86 | |
Inter-rater | 0.78 | 0.51 | 0.02 | 0.72 | 0.79 | 0.70 | ||
Overall | 0.90 | 0.73 | 0.04 | 0.90 | 0.92 | 0.87 | ||
G-coefficients | ||||||||
Non-dominant | Within-subject | 0.89 | 0.94 | 0.97 | 0.87 | 0.85 | 0.86 | |
Inter-rater | 0.83 | 0.25 | 0.24 | 0.67 | 0.73 | 0.76 | ||
Overall | 0.94 | 0.39 | 0.39 | 0.85 | 0.89 | 0.92 | ||
Dominant | Intercept | 6.32 *** | 106.47 *** | 17.23 ** | −8.03 *** | 15.69 *** | −3.65 * | |
n = 395 | (0.21) | (2.58) | (5.91) | (2.36) | (1.83) | (1.75) | ||
σ2rat | 0.00 | 3.17 | 0.00 | 0.00 | 0.00 | 0.58 | ||
σ2rep | 0.00 | 0.02 | 0.00 | 0.13 | 0.00 | 1.25 | ||
σ2subj | 0.77 | 74.92 | 25.21 | 100.03 | 61.76 | 46.20 | ||
σ2rep_rat | 0.00 | 0.00 | 1.48 | 0.00 | 0.00 | 0.00 | ||
Model and | σ2subj_rat | 0.17 | 51.27 | 1342.60 | 20.93 | 10.28 | 12.11 | |
variance | σ2subj_rep | 0.03 | 0.00 | 4.31 | 0.00 | 0.49 | 0.38 | |
components | σ2residual | 0.06 | 18.56 | 24.63 | 18.96 | 6.63 | 8.23 | |
Non-dominant | Intercept | 6.28 *** | 114.38 *** | 29.04 *** | −11.99 *** | 16.16 *** | −4.74 ** | |
n = 377 | (0.19) | (3.86) | (6.40) | (2.56) | (1.77) | |||
σ2rat | 0.00 | 20.71 | 0.00 | 1.20 | 0.00 | 0.08 | ||
σ2rep | 0.00 | 0.23 | 3.11 | 0.00 | 0.00 | 0.30 | ||
σ2subj | 0.62 | 37.73 | 302.47 | 97.08 | 53.01 | 48.27 | ||
σ2rep_rat | 0.00 | 0.00 | 0.80 | 0.00 | 0.12 | 0.00 | ||
σ2subj_rat | 0.07 | 94.76 | 935.13 | 30.81 | 11.60 | 6.90 | ||
σ2subj_rep | 0.02 | 3.66 | 5.39 | 2.83 | 2.25 | 0.18 | ||
σ2residual | 0.07 | 6.41 | 22.83 | 16.34 | 8.68 | 8.61 |
References
- Wren, T.A.; Gorton, G.E., 3rd; Ounpuu, S.; Tucker, C.A. Efficacy of clinical gait analysis: A systematic review. Gait Posture 2011, 34, 149–153. [Google Scholar] [CrossRef] [PubMed]
- Paulis, W.D.; Horemans, H.L.; Brouwer, B.S.; Stam, H.J. Excellent test-retest and inter-rater reliability for Tardieu Scale measurements with inertial sensors in elbow flexors of stroke patients. Gait Posture 2011, 33, 185–189. [Google Scholar] [CrossRef] [PubMed]
- van der Pas, S.C.; Verbunt, J.A.; Breukelaar, D.E.; van Woerden, R.; Seelen, H.A. Assessment of arm activity using triaxial accelerometry in patients with a stroke. Arch. Phys. Med. Rehabil. 2011, 92, 1437–1442. [Google Scholar] [CrossRef] [PubMed]
- McIntyre, A.; Viana, R.; Janzen, S.; Mehta, S.; Pereira, S.; Teasell, R. Systematic review and meta-analysis of constraint-induced movement therapy in the hemiparetic upper extremity more than six months post stroke. Top. Stroke Rehabil. 2012, 19, 499–513. [Google Scholar] [CrossRef] [PubMed]
- Felix, K.; Gain, K.; Paiva, E.; Whitney, K.; Jenkins, M.E.; Spaulding, S.J. Upper Extremity Motor Learning among Individuals with Parkinson’s Disease: A Meta-Analysis Evaluating Movement Time in Simple Tasks. Parkinson’s Dis. 2012, 2012, 589152. [Google Scholar] [CrossRef] [PubMed]
- El-Zayat, B.F.; Efe, T.; Heidrich, A.; Wolf, U.; Timmesfeld, N.; Heyse, T.J.; Lakemeier, S.; Fuchs-Winkelmann, S.; Schofer, M.D. Objective assessment of shoulder mobility with a new 3D gyroscope—A validation study. BMC Musculoskelet. Disord. 2011, 12, 168. [Google Scholar] [CrossRef] [PubMed]
- Bohannon, R.W.; Smith, M.B. Interrater reliability of a modified Ashworth scale of muscle spasticity. Phys. Ther. 1987, 67, 206–207. [Google Scholar] [CrossRef] [PubMed]
- McCrea, P.H.; Eng, J.J.; Hodgson, A.J. Biomechanics of reaching: Clinical implications for individuals with acquired brain injury. Disabil. Rehabil. 2002, 24, 534–541. [Google Scholar] [CrossRef] [PubMed]
- Alt Murphy, M.; Murphy, S.; Persson, H.C.; Bergstrom, U.B.; Sunnerhagen, K.S. Kinematic Analysis Using 3D Motion Capture of Drinking Task in People With and Without Upper-extremity Impairments. J. Vis. Exp. 2018. [Google Scholar] [CrossRef] [PubMed]
- Alt Murphy, M.; Willen, C.; Sunnerhagen, K.S. Kinematic variables quantifying upper-extremity performance after stroke during reaching and drinking from a glass. Neurorehabil. Neural Repair 2011, 25, 71–80. [Google Scholar] [CrossRef] [PubMed]
- de los Reyes-Guzman, A.; Gil-Agudo, A.; Penasco-Martin, B.; Solis-Mozos, M.; del Ama-Espinosa, A.; Perez-Rizo, E. Kinematic analysis of the daily activity of drinking from a glass in a population with cervical spinal cord injury. J. Neuroeng. Rehabil. 2010, 7, 41. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ustinova, K.I.; Goussev, V.M.; Balasubramaniam, R.; Leven, M.F. Disruption of coordination between arm, trunk, and center of pressure displacement in patients with hemiparesis. Motor Control 2004, 8, 139–159. [Google Scholar] [CrossRef] [PubMed]
- Johansson, G.M.; Grip, H.; Levin, M.F.; Hager, C.K. The added value of kinematic evaluation of the timed finger-to-nose test in persons post-stroke. J. Neuroeng. Rehabil. 2017, 14, 11. [Google Scholar] [CrossRef]
- Gladstone, D.J.; Danells, C.J.; Black, S.E. The fugl-meyer assessment of motor recovery after stroke: A critical review of its measurement properties. Neurorehabil. Neural Repair 2002, 16, 232–240. [Google Scholar] [CrossRef] [PubMed]
- Fugl-Meyer, A.R.; Jaasko, L.; Leyman, I.; Olsson, S.; Steglind, S. The post-stroke hemiplegic patient. 1. a method for evaluation of physical performance. Scand. J. Rehabil. Med. 1975, 7, 13–31. [Google Scholar] [PubMed]
- Bergeron, D.; Vermette, A.; De La Sablonniere, J.; Cayer, A.M.; Laforce, R.; Bouchard, R.W. Finger-to-Nose Test Findings in Alzheimer’s Disease. J. Alzheimers Dis. 2017, 55, 1335–1337. [Google Scholar] [CrossRef]
- de Jong, L.D.; Nieuwboer, A.; Aufdemkampe, G. The hemiplegic arm: Interrater reliability and concurrent validity of passive range of motion measurements. Disabil. Rehabil. 2007, 29, 1442–1448. [Google Scholar] [CrossRef]
- Totty, M.S.; Wade, E. Muscle Activation and Inertial Motion Data for Noninvasive Classification of Activities of Daily Living. IEEE Trans. Bio-Med. Eng. 2018, 65, 1069–1076. [Google Scholar]
- Perez, R.; Costa, U.; Torrent, M.; Solana, J.; Opisso, E.; Caceres, C.; Tormos, J.M.; Medina, J.; Gomez, E.J. Upper limb portable motion analysis system based on inertial technology for neurorehabilitation purposes. Sensors 2010, 10, 10733–10751. [Google Scholar] [CrossRef]
- Shavelson, R.J.; Webb, N.M.; Rowley, G.L. Generalizability theory. Am. Psychol. 1989, 44, 922–932. [Google Scholar] [CrossRef]
- Öhberg, F.; Lundström, R.; Grip, H. Comparative analysis of different adaptive filters for tracking lower segments of a human body using inertial motion sensors. Meas. Sci. Technol. 2013, 24, 12. [Google Scholar] [CrossRef]
- Ertzgaard, P.; Ohberg, F.; Gerdle, B.; Grip, H. A new way of assessing arm function in activity using kinematic Exposure Variation Analysis and portable inertial sensors—A validity study. Man. Ther. 2016, 21, 241–249. [Google Scholar] [CrossRef] [PubMed]
- El-Gohary, M.; McNames, J. Human Joint Angle Estimation with Inertial Sensors and Validation with A Robot Arm. IEEE Trans. Bio-Med. Eng. 2015, 62, 1759–1767. [Google Scholar] [CrossRef] [PubMed]
- Wu, G.; van der Helm, F.C.; Veeger, H.E.; Makhsous, M.; Van Roy, P.; Anglin, C.; Nagels, J.; Karduna, A.R.; McQuade, K.; Wang, X.; et al. ISB recommendation on definitions of joint coordinate systems of various joints for the reporting of human joint motion—Part II: Shoulder, elbow, wrist and hand. J. Biomech. 2005, 38, 981–992. [Google Scholar] [CrossRef] [PubMed]
- Soderkvist, I.; Wedin, P.A. Determining the movements of the skeleton using well-configured markers. J. Biomech. 1993, 26, 1473–1477. [Google Scholar] [CrossRef]
- de Vet Henrica, C.W.; Terwee Caroline, B.; Mokkink Lidwine, B.; Knol, D.L. Measurement in Medicine: A Practical Guide; Cambridge University Press: Cambridge, UK; New York, NY, USA, 2011; p. x. 338p. [Google Scholar]
- Salvia, J.; Ysseldyke, J.E.; Witmer, S. Assessment in Special and Inclusive Education, 13th ed.; Cengage Learning: Boston, MA, USA, 2017. [Google Scholar]
- Molina Rueda, F.; Rivas Montero, F.M.; Perez de Heredia Torres, M.; Alguacil Diego, I.M.; Molero Sanchez, A.; Miangolarra Page, J.C. Movement analysis of upper extremity hemiparesis in patients with cerebrovascular disease: A pilot study. Neurologia 2012, 27, 343–347. [Google Scholar] [CrossRef]
- Alt Murphy, M.; Willen, C.; Sunnerhagen, K.S. Responsiveness of upper extremity kinematic measures and clinical improvement during the first three months after stroke. Neurorehabil. Neural Repair 2013, 27, 844–853. [Google Scholar] [CrossRef]
- Santos, G.L.; Russo, T.L.; Nieuwenhuys, A.; Monari, D.; Desloovere, K. Kinematic Analysis of a Drinking Task in Chronic Hemiparetic Patients Using Features Analysis and Statistical Parametric Mapping. Arch. Phys. Med. Rehabil. 2018, 99, 501–511. [Google Scholar] [CrossRef]
- Lee, J.A.; Hwang, P.W.; Kim, E.J. Upper extremity muscle activation during drinking from a glass in subjects with chronic stroke. J. Phys. Ther. Sci. 2015, 27, 701–703. [Google Scholar] [CrossRef] [Green Version]
- Bernstein, N.A. The Co-Ordination and Regulation of Movements; Pergamon Press: London, UK, 1967. [Google Scholar]
- Rodrigues, M.R.; Slimovitch, M.; Chilingaryan, G.; Levin, M.F. Does the Finger-to-Nose Test measure upper limb coordination in chronic stroke? J. Neuroeng. Rehabil. 2017, 14, 6. [Google Scholar] [CrossRef]
- Maurel, N.; Diop, A.; Gouelle, A.; Alberti, C.; Husson, I. Assessment of upper limb function in young Friedreich ataxia patients compared to control subjects using a new three-dimensional kinematic protocol. Clin. Biomech. 2013, 28, 386–394. [Google Scholar] [CrossRef]
- Jeon, H.J.; An, S.; Yoo, J.; Park, N.H.; Lee, K.H. The effect of Monkey Chair and Band exercise system on shoulder range of motion and pain in post-stroke patients with hemiplegia. J. Phys. Ther. Sci. 2016, 28, 2232–2237. [Google Scholar] [CrossRef] [Green Version]
- Eriks-Hoogland, I.E.; de Groot, S.; Post, M.W.; van der Woude, L.H. Passive shoulder range of motion impairment in spinal cord injury during and one year after rehabilitation. J. Rehabil. Med. 2009, 41, 438–444. [Google Scholar] [CrossRef] [Green Version]
- Muller, R.; Buttner, P. A critical discussion of intraclass correlation coefficients. Stat. Med. 1994, 13, 2465–2476. [Google Scholar] [CrossRef]
- Thies, S.B.; Tresadern, P.A.; Kenney, L.P.; Smith, J.; Howard, D.; Goulermas, J.Y.; Smith, C.; Rigby, J. Movement variability in stroke patients and controls performing two upper limb functional tasks: A new assessment methodology. J. Neuroeng. Rehabil. 2009, 6, 2. [Google Scholar] [CrossRef]
Side | Reliability | Cycle Time | Elbow FE | Elbow R | Shoulder FE | Shoulder AbAd | Shoulder R | |
---|---|---|---|---|---|---|---|---|
Dominant | Within-subject | 0.89 | 0.91 | 0.97 | 0.89 | 0.92 | 0.91 | |
Inter-rater | 0.84 | 0.77 | 0.15 | 0.78 | 0.67 | 0.73 | ||
G-coefficients | Overall | 0.94 | 0.88 | 0.26 | 0.91 | 0.83 | 0.87 | |
Non-dominant | Within-subject | 0.91 | 0.94 | 0.96 | 0.90 | 0.92 | 0.94 | |
Inter-rater | 0.83 | 0.62 | 0.30 | 0.74 | 0.76 | 0.82 | ||
Overall | 0.94 | 0.77 | 0.47 | 0.88 | 0.87 | 0.92 | ||
Dominant | Intercept | 2.35 s *** | 58.66° *** | −53.66° *** | 22.42° *** | −20.08° *** | 20.72° *** | |
n = 397 | (0.12) | (4.14) | (4.70) | (2.81) | (1.72) | (1.89) | ||
σ2rat | 0.00 | 13.71 | 0.00 | 3.99 | 0.00 | 0.29 | ||
σ2rep | 0.00 | 0.00 | 5.90 | 0.76 | 0.62 | 0.14 | ||
σ2subj | 0.28 | 186.75 | 113.81 | 107.42 | 48.16 | 60.17 | ||
Model and | σ2rep_rat | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | |
variance | σ2subj_rat | 0.03 | 37.48 | 629.23 | 17.02 | 18.76 | 16.16 | |
components | σ2subj_rep | 0.01 | 2.72 | 1.10 | 2.20 | 0.57 | 0.92 | |
σ2residual | 0.02 | 6.32 | 14.05 | 8.43 | 4.55 | 6.49 | ||
Non-dominant | Intercept | 2.31 s *** | 61.35° *** | −54.47° *** | 21.87° *** | −16.26° *** | 19.94° *** | |
n = 379 | (0.13) | (4.04) | (4.14) | (2.64) | (2.69) | (2.13) | ||
σ2rat | 0.00 | 9.61 | 0.00 | 3.57 | 4.35 | 0.00 | ||
σ2rep | 0.00 | 0.30 | 3.94 | 0.02 | 0.00 | 0.06 | ||
σ2subj | 0.29 | 173.26 | 148.50 | 87.90 | 85.66 | 79.07 | ||
σ2rep_rat | 0.00 | 0.00 | 0.00 | 0.14 | 0.09 | 0.00 | ||
σ2subj_rat | 0.03 | 90.53 | 338.92 | 20.29 | 19.94 | 12.80 | ||
σ2subj_rep | 0.00 | 1.89 | 2.41 | 1.24 | 1.60 | 1.42 | ||
σ2residual | 0.03 | 4.74 | 14.53 | 6.52 | 3.47 | 4.69 |
Side | Reliability | Cycle Time | Elbow FE | Elbow R | Shoulder FE | Shoulder AbAd | Shoulder R | |
---|---|---|---|---|---|---|---|---|
Dominant | Within-subject | 0.92 | 0.88 | 0.97 | 0.85 | 0.80 | 0.90 | |
Inter-rater | 0.81 | 0.47 | 0.002 | 0.67 | 0.72 | 0.78 | ||
G-coefficients | Overall | 0.93 | 0.68 | 0 | 0.86 | 0.93 | 0.90 | |
Non-Dominant | Within-subject | 0.90 | 0.96 | 0.96 | 0.87 | 0.90 | 0.87 | |
Inter-rater | 0.84 | 0.42 | 0.14 | 0.72 | 0.81 | 0.60 | ||
Overall | 0.95 | 0.60 | 0.23 | 0.87 | 0.93 | 0.79 | ||
Dominant | Intercept | 5.65 s *** | 90.76° *** | 20.09° *** | 5.68° ** | 14.69° *** | −5.00° ** | |
n = 397 | (0.20) | (2.77) | (5.62) | (1.76) | (1.64) | (1.68) | ||
σ2rat | 0.00 | 0.00 | 0.00 | 0.00 | 0.91 | 0.00 | ||
σ2rep | 0.00 | 2.38 | 0.00 | 0.16 | 0.00 | 1.04 | ||
σ2subj | 0.71 | 100.31 | 0.00 | 53.09 | 41.88 | 48.74 | ||
Model and | σ2rep_rat | 0.00 | 0.88 | 0.00 | 0.00 | 0.14 | 0.00 | |
variance | σ2subj_rat | 0.10 | 92.30 | 1260.94 | 16.06 | 4.53 | 10.01 | |
components | σ2subj_rep | 0.01 | 0.00 | 2.08 | 1.22 | 0.57 | 0.77 | |
σ2residual | 0.06 | 23.05 | 36.25 | 10.46 | 11.02 | 4.44 | ||
Non-dominant | Intercept | 5.68 s *** | 97.79° *** | 24.75° *** | 2.94° | 15.84° *** | −3.15° | |
n = 376 | (0.19) | (2.96) | (5.38) | (2.37) | (1.74) | (1.62) | ||
σ2rat | 0.00 | 0.00 | 0.00 | 0.22 | 0.00 | 0.00 | ||
σ2rep | 0.00 | 0.03 | 3.67 | 0.00 | 0.00 | 0.00 | ||
σ2subj | 0.62 | 99.10 | 124.19 | 90.38 | 53.51 | 39.08 | ||
σ2rep_rat | 0.00 | 0.40 | 0.00 | 0.82 | 0.09 | 0.21 | ||
σ2subj_rat | 0.05 | 133.03 | 832.17 | 24.28 | 6.91 | 19.92 | ||
σ2subj_rep | 0.01 | 1.36 | 9.89 | 4.21 | 0.68 | 1.33 | ||
σ2residual | 0.07 | 7.43 | 23.90 | 11.52 | 5.94 | 7.22 |
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Öhberg, F.; Bäcklund, T.; Sundström, N.; Grip, H. Portable Sensors Add Reliable Kinematic Measures to the Assessment of Upper Extremity Function. Sensors 2019, 19, 1241. https://doi.org/10.3390/s19051241
Öhberg F, Bäcklund T, Sundström N, Grip H. Portable Sensors Add Reliable Kinematic Measures to the Assessment of Upper Extremity Function. Sensors. 2019; 19(5):1241. https://doi.org/10.3390/s19051241
Chicago/Turabian StyleÖhberg, Fredrik, Tomas Bäcklund, Nina Sundström, and Helena Grip. 2019. "Portable Sensors Add Reliable Kinematic Measures to the Assessment of Upper Extremity Function" Sensors 19, no. 5: 1241. https://doi.org/10.3390/s19051241