Background
Methods
Research questions
Types of participants
Outcome measures
Criteria for studies inclusion
Eligibility
Data extraction
Clinical data
Technical data
Results
Study inclusion and assessment
Participant characteristics
Author | Study type | Aims | Setting | Sample Size | Mean Age (yrs) | Inclusion Criteria | Exclusion Criteria | Reference Standard |
---|---|---|---|---|---|---|---|---|
[25] Birmingham A. T. et al. (1985) | Survey | To evaluate the variation of tremor frequency and amplitude in relation to the age | Laboratory | 109 | n = 22 (7–9), n = 28 (9–11), n = 24 (11–13), n = 22 (13–15), n = 13 (16–18) | To be attending specific schools or fit classes | NA | NA |
[24] Avi Sadeh et al. (1994) [Study 1] | Lab-based validation and calibration study | To develop a new sleep-wake scoring algorithm | Laboratory | 16 | 13.8 ± 1.9 | Volunteers | NA | NA |
[27] Deutsch K. M. et al. (2006) | Observational study | To investigate the mechanical and neural components of postural finger tremor | Laboratory | 39 | n = 20 (6.4 ± 3), n = 19 (10.5 ± 0.3), n = 21 (20.8 ± 1.4) | Volunteers | Neurological disorders, influencing tremor | NA |
[34] Graves L.E.S. et al. (2008) | Observational study | To examine the contribution of the upper limb and total body movement to adolescents’ energy expenditure whilst playing videogames | Laboratory | 13 | 11–17 | Good health picture | NA | NA |
[17] Davila E. M. (2011) | Observational study | To evaluate the influence of wearing AMs on the D vs ND wrists on measurements of free living PA | Laboratory + outpatient | 20 | 12–17 | 1) volunteer participants from Bozeman, Montana, 2) 12–17 yrs | NA | NA |
[21] Phillips L. R. S. et al. (2012) | Lab-based validation and calibration study | To develop physical activity intensity cut-points for use with GENEA accelerometer | Laboratory | 44 | 10.9 ± 1.9 | NA | NA | NA |
[28] MacArthur B. et al. (2014) | 2 × 2 mixed design with random allocation. | To measure percentage of time engaged in MVPA and estimated EE with accelerometry in playing AVG vs unstructured OP | ELC playground, ELC room | 16 (8 OP vs. 8 AVG) | OP = 6.6 ± 0.7, AVG = 6.3 ± 0.9 | 1) good health, 2) healthy weight (BMI percentile = 5–85), 3) no limit for physical activity. | Grass allergies. Skin sensitivity to light. Failure to complete all session within a 3-week period. | NA |
[19] Lemmens R. J. M. et al. (2015) | Cross sectional study | To evaluate the reliability of arm-hand tasks accelerometer records | Laboratory | 32 | n = 16 children (8.5 ± 1.7), n = 16 (14.6 ± 1.5) | Volunteers | Motor problems with arm, hand or shoulder | NA |
[31] Kaneko M. et al. (2015) | Observational Study | To quantify age-appropriate developmental changes of SNS | Laboratory | 233 | 4–12 | Student at the Fukuoka Municipal Elementary School | NA | NA |
[35] Dadashi F. et al. (2015) [Group 2] | Observational study | To characterise front-crawl swimming skills | Outdoor pool | 9 | 16.0 ± 1.8 | Recreational swimmers | NA | NA |
[36] Mackintosh K.A. et al. (2016) | Observational study | To validate and compare ANNs | Laboratory, semi-structured setting | 27 | 10.8 ± 1.0 | Volunteers recruited via a local primary school. The children attended the the laboratory only if: 1) rested state, 2) at least 2 h postprandial, 3) strenous exercise and coffeine avoided in the previous 24 h | NA | NA |
Author | Study type | Aims | Setting | Sample Size | Disease | Mean Age (yrs) | Inclusion Criteria | Exclusion Criteria | Reference Standard |
---|---|---|---|---|---|---|---|---|---|
[23] Floyd A. G. et al. (2007) | Multy-centered study | To analyze the UL motor physiology | Laboratory | 15 | NP-C | 25 ± 10 | 1) = > 12 years of age, 2) confirmed diagnosis of NP-C by abnormal cholesterol esterification and abnormal filipin staining | 1) concurrent enrolment in other clinical trials, 2) drugs or diet supplements, interfering with digestive absorption of study medication, 3) significant history of gastrointestinal disorders, HIV or hepatitis, 4) not comply with study procedures | EDSS |
[22] Gordon A. M. et al. (2007) | Single-blinded randomized control study | To examine the efficacy of the HABIT | Summer camp | 20 (10 HABIT vs 10 CG) | UCP | Total sample = 9.6 ± 6.0, HABIT = 4.5–13.7, CG = 3.9–10.6 | 1) ability to extend the wrist> 20° and the fingers at the metacarpophalangeal joints> 10° from full flexion, 2) JTHF: > 50% difference between the involved and the non-involved hand, 3) ability to lift the involved arm> 6 in., 4) BBIT = mean score +/− < 1DS | 1) health problems unassociated with CP, 2) current/untreated seizures, 3) visual problems interfering with the intervention or testing, 4) MAS > 3.5, 5) orthopaedic surgery on the involved upper extremity, 6) dorsal rhizotomy, 7) botox therapy in the UL in the prior 6 months or within the period of study, 8) intrathecal baclofen. | AHA, BOT-2, CFUS, JTHF |
[29] Strohrmann C. et al. (2013) | Longitudinal study | i) to monitor children activities in daily life, ii) to evaluate the use of body worn sensors for motor assessment in children | Laboratory | 4 | CP (2), acquired stroke (2) | 10.5 ± 2,12 | 1) neurological diagnosis leading to stationary stay, 2) age = 5–18 years, 3) cognitive ability to understand the aim of the tasks | NA | Motor Capacity Assessment |
[20] Zoccolillo L. et al. (2015) | Cross-sectional experimental quantitative study | i) to monitor physical activity during VGT vs conventional therapy, ii) to quantify if VGT enhances number of movements | Outpatient + inpatient | 8 | UCP | 6,6 ± 1,4 | 1) UCP, 2) 4–14 yrs., 3) GMFCS: I-IV, 4) any Xbox with Kinect at home. | 1) IQ < 35, 2) severe comorbidities, 3) incapacity to stand, even with an external support. | QUEST, ABILHAND-kids |
[18] Sokal B. et al. (2015) | Cross sectional, observational design | i) to evaluate the UL activity, ii) to compare the use of the affected arm between children and adult with hemiplegia | Not reported | 28 | UCP | 3.9 ± 1.7 | NA | 1) serious or recurring medical complications, 2) spasticity medication within the last 3 months, 3) previous paediatric CIMT, 4) fixed contractures in the affected-arm, 5) invalid accelerometer records (insufficient time, only 1 wrist, unrealistic records, malfunction) | PMAL-R, PAFT |
[26] Bergamini E. (2014) | Three experimental sessions | i) to identify a biomechanical performance indicators of wheelchair propulsion, ii) develop and assess the efficacy of a specific training program | Basketball court | 12 (6 EG vs 6 CG) | Paraplegia (4), myelomeningocele (3), poliomyelitis (2), spastic diplegia (1), below-knee amputation (1), knee arthroprothesis (1) | Total sample = 17.1 ± 2.7, EG = 13–20, CG = 12–20 | At least two years of previous wheelchair basketball experience. | Medical contraindications | NA |
[32] Kaneko M. et al. (2016) | Observational study | i) to establish a quantitative evaluation system of soft neurological signs | Laboratory | 33 | ADHD | 7–11 | 1) patients of the Kurume University Hospital, 2) positive DSM-IV criteria for ADHD diagnosis, 3) WISC-III > 70 | NA | NA |
[33] Le Moing A.G. et al. (2016) | Observational study | i) to highlight the feasibility of quantifying the range of upper limb movements | Laboratory | 7 | DMD | 18.5+/− 5.5 | 1) patients of the Institute of Myology, 2) age > 10 years old, 3) non-ambulant, 4) able to sit for at least 3 h in the wheelchair | 1) cognitive impairment, 2) occurrence of neurological/inflammatory/infectious/endocrine/acute orthopaedic disease in the precious month, 3) scheduled surgery within 3 weeks of inclusion date, 4) surgery of the upper limbs in the previous three months | MyoSet (MyoPinch, MyoGrip and MyoPlate), BBT, Minnesota Test |
[30] O’Neil M.E. et al. (2016) | Observational study | i) to evaluate the inter-instrument reliability and concurrent validity of 3 accelerometer-based motion sensors for measuring PA intensity | Clinical standardized setting | 57 | CP: hemiplegia (29), diplegia (26), quadriplegia (3) | 12.5 ± 3.3 | 1) GMFCS = I-III, 2) ambulatory children, 3) 6–20 years old, 4) able to follow instructions and protocol directions, 5) able to wear 3 pairs of accelerometers and 1 portable indirect calorimeter. | 1) recent musculoskeletal injuries, limiting their PA levels, 2) orthopaedic surgery within the precious 6 months, 3) botulinum toxin or phenol injections within the previous three months, 4) previous unstable medical conditions limiting PA levels, 5) unstable emotional or behavioural status. | NA |
[37] Cocker-Bolt P. et al. (2016) | Prospective pre-test/post-test study | To determine the feasibility and use accelerometers before, during and after a CIMT program | Outpatient + Laboratory | 12 | UCP | 4.9 ± 1.33 | 1) UCP, 2) able to use the affected UL as a gross assist during play and self-care activities, 3) no significant developmental delays, 4) ambulatory, 5) no additional health impairments | 1) significant intellectual disabilities, 2) seizure disorders, 3) botulinum toxin injections in the previous 6 months | MA2 |
Forms of assessment
Upper limb accelerometer applications
Author | Sensors Number | Sensors Type & Make | Placement | Wear time | Sample frequency |
---|---|---|---|---|---|
[25] Birmingham A. T. et al. (1985) | 2 | Accelerometers (Bruel and Kjaer type 4367). | Terminal phalanx of each middle finger | 3 min for each hand | 5-s epoch |
[24] Avi Sadeh et al. (1994) [Study 1] | 2 | Actigraphs (AMA-32, Ambulatory Monitoring, Inc., Ardsley, NY). | Each wrist | 2 nights (about 7 h to night) | 1-min epochs. |
[27] Deutsch K. M. et al. (2006) | 2 | Uniaxial wireless accelerometers (Coulbourn T45–10, calibrated on each day of testing). | Dorsal surface of the tip of the distal segment of each index finger. | three 10-s consecutive trials, about 5 s breaks between trials. | 200 Hz |
[34] Graves L.E.S. et al. (2008) | 6 | 1) Actiheart (Cambridge Neurotechnology Cambridge, UK), 2) 4 uniaxial ActiGraph accelerometers (GT1M, Fort Walton Beach, FL, USA) | 1) on the skin at the base of the sternum, 2) on the midaxillary line of the right and left hip and on each forearm proximally from the wrist joint . | 60 min | 2) 30 Hz |
[17] Davila E. M. (2011) | 2 | Actical triaxial AMs (Respironics Co., Inc., Bend, OR, USA). | Dorsal side of each wrist | Full seven days (24 h/day). | 15-s epoch |
[21] Phillips L. R. S. et al. (2012) | 3 + 1 | Triaxial wireless accelerometers GeneActive (Unilever Discover, Colworth, UK) + ActiGraph GT1M (Actigraph, Pensacola, FL, USA). | Each wrist and + right hip (ActiGraph GT1M worn adjacent to the hip mounted GENEA) | Activities: 5 min; Lying supine: 10 min. | GENEA: 80 Hz, ActiGraph GT1M: 1 s epochs. |
[28] MacArthur B. et al. (2014) | 3 | Actical accelerometers (Actical, Philips Respironics Co. Inc., Bend, OR). | Each wrist + hip | 20 min | 15-s epoch |
[19] Lemmens R. J. M. et al. (2015) | 7 | Sensor devices, composed by a triaxial accelerometer, triaxial gyroscope, triaxial magnetometer (SHIMMER Research, Dublin, Ireland). | Chest + Dominant and non-dominant arm-hand: on the dorsal side of the hand, of the wrist and on the upper arm | Not specified. | 128 Hz |
[31] Kaneko M. et al. (2015) | 4 | Wearable sensors composed of three-axis acceleration and three-axis angular velocity sensors (WAA-006, WAA-010, ATR-Promotions, Kyoto, Japan) | Both hands and elbows | Four motor tasks: 10 s for each task | 100 Hz |
[35] Dadashi F. et al. (2016) [Group 2] | 3 | Waterproof IMUs (Physilog III, BioAGM, CH, 3D accelerometer, 3D gyroscope). | 2 IMUs placed on the dorsal side and distal end of the forearms, one on the sacrum. | Not specified. | 500 Hz |
[36] Mackintosh K.A. et al. (2016) | 9 | Triaxial accelerometer (Actigraph wGT3X+, Florida, USA) | On the lateral plane of each ankle, knee, hip, wrist, and centre of the chest. | 30 min | 100 Hz |
Author | Accelerometer data comparison | Differences between the two hands | Data cleaning | Threshold (cutoff frequency of filter applied on raw data) | Threshold to assess the intensity of arm movement |
---|---|---|---|---|---|
[25] Birmingham A. T. et al. (1985) | RMS of tremor amplitude, dominant peak and its frequency. | For rest tremor, amplitude in the dominant hand was significantly lower in adolescence and early adult life than in childhood, for the non-dominant hand the statistically significant difference was sustained to later life. For work tremor, dominant hand frequency declined significantly with age, both hands continue to decline in adulthood. | Frequency analysis of the tremor waveform was filtered to remove frequencies above 50 Hz to prevent alias contamination | 50 Hz | NA |
[24] Avi Sadeh et al. (1994) [Study 1] | Accelerometric data matched with PSG scoring performed to develop the scoring algorithm: PS probability of sleep | The mean activity level of the dominant wrist was significantly higher than that of the nondominant wrist during PSG-determined sleep (6.84 vs. 6.16), as well as during wakefulness (25.8 vs. 22.3). | NA | NA | NA |
[27] Deutsch K. M. et al. (2006) | The peak frequency within two frequency bands (5–15 Hz and 15–30 Hz) and the proportion of power exhibited at the peak frequency determined (based on power spectral density calculated using Welch’s averaged periodogram method). | The peak frequency of the finger of the dominant hand (21.4 Hz) was higher than nondominant hand (20.7 Hz) in the 15–30 Hz frequency band. No significant differences in proportion of power exhibited at peak frequency within the 5–15 Hz of postural tremor as a function of age, hand dominance or hand configuration. Postural tremor of nondominant hand was significantly more regular than dominant hand. | Band-pass filtered | 1 Hz - 50 Hz | NA |
[34] Graves L.E.S. et al. (2008) | Means and standard deviations of activity counts (counts/min) | Activity of the dominant limb was significantly greater than non-dominant during tennis and bowling (P < 0.001) and non-dominant limb activity was significantly greater during boxing than bowling or tennis (P < 0.001). Activity counts from the left wrist for tennis and boxing (r = 0.710 and 0.744, P < 0.01) and the right wrist for boxing (r = 0.586, P < 0.05) were significantly correlated with EE. | Band pass filtering | 0.21–2.28 Hz | NA |
[17] Davila E. M. (2011) | Data Trasformation: AEE, Time. Data Summarization Characteristics: Bouts Duration, Intensity Thresholds. | No statistical differences between outcome variables for any bout duration (1, 5, 10 min) within L and MV intensity categories between AMs (D versus ND, LW versus RW) or model (1R versus 2R). Dominant and RW AMs were no-significantly higher than ND and LW, respectively, within MVPA intensity. In contrast, ND and LW AMs were non-significantly higher than D and RW within L intensity PA. Identical results within gender. | Quantity control checks were performed to identify periods on non-wear. | NA | Light (AEE < 0.05 kcals/kg/min), moderate (0.05 < AEE < 0.09 kcals/kg/min), vigorous (AEE ≥ 0.10 kcals/kg/min). |
[21] Phillips L. R. S. et al. (2012) | VM with gravity-substracted. | Both sides demonstrated good criterion validity (right: r = 0.9, left: r = 0.91) and good concurrent validity (right: r = 0.83, left: r = 0.845). ROC analysis proved GENEA monitors able to successfully discriminate among all intensity levels. | NA | NA | Sedentary (< 1.5 METs), light (1.5–2.99 METs), moderate (3–5.99 METs) and vigorous (≥ 6 METs). The accelerometer counts for activities were coded into binary indicator variables (0 or 1) based on intensity. |
[28] MacArthur B. et al. (2014) | Percentage of time in MVPA calculated by summing the number of 15-s intervals in which the activity counts were ≥ 574 counts/15 s. | The accelerometers placed on the wrists did not find differences in the conditions in percentage MVPA (right: 48.8 ± 29.5%, left: 47.6 ± 28.8%). | NA | NA | MVPA: activity counts ≥574 counts/15 s. |
[19] Lemmens R. J. M. et al. (2015) | ICC parameter (based on VM). | Within-subject reliability calculated for the 2 arm hands separately, median ICCs ranged between 0.68–0.92. Between subject reliability for the 2 arm hands separately, median ICCs ranged between 0.61–0.90. | Zero time-phase, low-pass filtered | 1.28 Hz | NA |
[31] Kaneko M. et al. (2015) | Postural stability of the hands and elbows, rotational speed, mirror movement, two parameters of bimanual symmetry, compliance | All indices had a tendency to increase with age. | Low-pass filter | 6 Hz | NA |
[35] Dadashi F. et al. (2016) [Group 2] | Average propulsive phases of right and left arms, pull and push phases (Δpull, Δpush), sum of aerial recovery and entry catch phases (ΔNProp), index of coordination (IdC). | By increasing the velocity, the duration of arm under-water phases (Δpull + Δpush) and accordingly IdC did not change significantly. G2 group used 2,8% lower catch-up pattern (P < 0,01) by increasing the arm under-water phases (P < 0.016) and using 6.5 more arm stroke (P < 0.001). No changes in the stroke length and cycle velocity variation were observed (P > 0.22). | NA | NA | NA |
[36] Mackintosh K.A. et al. (2016) | Mean and variance of the accelerometer counts in each 15 s window. These extracted features were used as inputs into the ANNs, a specific type of machine learning model. RMSE. | The ANNs for left and right wrist accelerometers had a lower correlations with predicted EE. No significant differences in RMSE analysis. Despite significant advantages in terms of compliance, they could lead to potentially marginal losses in EE prediction accuracy. | NA | NA | 1,4% of collected data were removed when EE < 0,5 MET (measured with MetaMax 3B) |
Author | Sensors Number | Sensors Type & Make | Placement | Wear Time | Sample frequency |
---|---|---|---|---|---|
[23] Floyd A. G. et al. (2007) | 2 | Piezoresistive uniaxial accelerometers with linear sensitivities of 4.5 mV/g in the biological tremor range (0–25 Hz) | Over the dorsum of both hands | Multiple recording and total recording time lasted 1–2 h | 300 Hz |
[22] Gordon A. M. et al. (2007) | 2 | Accelerometers (Manufacturing Technology Inc. Fort Walton Beach, FL, model 7164) | Each wrist | During the AHA test session | 10 Hz |
[29] Strohrmann C. et al. (2013) | 10 | ETH Orientation Sensor (ETHOS) = IMU composed by a 3D accelerometer, a 3D gyroscope and a 3D digital compass. Not commercially available. | Upper (wrists and upper arms) and lower extremities (upper legs and feet) and the trunk. | 1 h, once per week over a course of four weeks. | 100 Hz |
[20] Zoccolillo L. et al. (2015) | 5 | Wireless triaxial accelerometers (Trigno, Delsys®). | Posterior part of forearms, of shanks and of lower trunk in correspondence of the centre of mass (L2-L3). | During 5 continuous minutes of video-game based therapy and 5 min of CT. | Not specified |
[18] Sokal B. et al. (2015) | 2 | Biaxial wireless accelerometers (Model 71,256, Actigraph, Pensacola, FL) | Dorsal side of both wrists just above the styloid process | During waking hours for at least 9 h daily for 3 consecutive days after the testing session. | 10 Hz, integrated over a user-specified epoch (2 s). |
[26] Bergamini E. (2014) | 3 | IMUs (Opal, APDM Inc., Portland, Oregon, USA). | Both wrists and backrest of the wheelchair. | Time was manually recorded. Total time not reported. | 128 Hz |
[32] Kaneko M. et al. (2016) | 4 | Acceleration and angular velocity sensors (WAA-006, WAA-010, ATR-Promotions, Kyoto, Japan) | Both hands and elbows | Two motor tasks (imitative motor task and a maximal-effort motor task): 10 s for each task | 100 Hz |
[33] Le Moing A.G. et al. (2016) | 2 | Watch-like devices contained a three-axis accelerometer, a three-axis gyroscope, and a three-axis magnetometer | On each wrist | At least 30 min to complete all the tasks, without concerning potential resting period | NA |
[30] O’Neill M.E. et al. (2016) | 6 | 1) StepWatch activity monitor (uniaxial), 2) Actigraph GT3X (triaxial), 3) BodyMedia SenseWear Pro Armband (triaxial). | 1) superior to the left/right malleolus, 2) on a waist elastic belt superior to the right/left iliac crest, 3) dorsal side of each upper arm at the midbelly of the triceps muscle | During each data collection, lasting 2–2,5 h | 1 s for ActiGraph, 3 s for StepWatch, and 60 s for SenseWear. |
[37] Coker-Bolt P. et al. (2017) | 2 | Triaxial Actigraph GT9X Link (Actigraph, Pensacola, FL) | On each wrist | 6 h a day before and after the CIMT program (tot: 12 h) | 30 Hz |
Author | Accelerometer data comparison | Differences between the two hands | Data cleaning | Threshold (cutoff frequency of filter applied on raw data) | Threshold to assess the intensity of arm movement |
---|---|---|---|---|---|
[23] Floyd A. G. et al. (2007) | Side-to-side relationship of tremor amplitude, peak tremor frequencies and amplitude variability. | Action tremor amplitudes were relatively symmetric between the dominant and non-dominant hands, postural tremor was not symmetric bilaterally (3 of 8 patients were unilateral), amplitudes of bilateral cases correlated within subjects. | In the FTN trials only, frequencies below 2 Hz were excluded | 2 Hz | NA |
[22] Gordon A. M. et al. (2007) | Percentage of hand use (activity counts) | The percentage of use of involved extremity remain the same in controls, 70% of the task performance, while increased from 62.6 to 77.8% for the children who received HABIT (not correlate with the change in AHA scores). Use of the non-involved extremity remained the same across testing sessions in both groups. | NA | NA | NA |
[29] Strohrmann C. et al. (2013) | TIME, mean value of MI, MIV, DF, SM, ARE, RANG, ArmSync, gait parameters (all based on VM). | MIV is larger for the unaffected hand, the energy associated to the dominant frequency of the affected hand vs. unaffected hand was much lower, the SM parameter of the unaffected side vs. affected side was twofold. | Low-pass filtered | 45 Hz | NA |
[20] Zoccolillo L. et al. (2015) | RMS of acceleration. | Hemiparetic side was moved less than healthy side. In VGT the paretic side was moved − 20 ± 13% less than the other side, while this difference was not significant in CT (− 10 ± 28%). | Low-pass filtered and after the mean substraction for removing the contribution of gravity acceleration. | 20 Hz | NA |
[18] Sokal B. et al. (2015) | Duration SV, duration ratio SV, intensity SV, intensity ratio SV. | Partecipants moved their more-affected arm for 55.7% and their less-affected arm for 64.9%, ratio 0.86. The intensity of more-affected arm was 41.3 counts/s and for less-affected arm was 60.5, ratio 0.71. | Segments when partecipants appeared to have removed the accelerometers were removed. | NA | Raw values for each 2 s recording epoch were dichotomized around a low threshold (i.e., 2) with above-threshold values set to a positive costant and at- or below-threshold values set to zero. |
[26] Bergamini E. (2014) | Symmetry index, a peak of the acceleration magnitude and CV (all based on VM). | Symmetry index: - CG: ES2 (48.92%) and ES3 (47.86%), − EG: ES2 (47.77%) and ES3 (48.62%). These values indicate good symmetry. | Low-pass filtered | 12 Hz | NA |
[32] Kaneko M. et al. (2016) | Rotational speed, mirror movement, postural stability of rotating elbow, temporal change of rotational size in each index, bimanual symmetry, compliance. | All scores of ADHD children was lower than TD children. In bimanual symmetry the score of ADHD children increased with age and was significantly different to TD aged 8 and 10 years old. The variability of children’s score in compliance and temporal change of rotational size in ADHD vs. TD was larger. | Low-pass filtered | 6 Hz | NA |
[33] Le Moing A.G. et al. (2016) | Norm of the angular velocity, ratio of the vertical component of the acceleration, model-based computed power, elevation rate | Not find any side effect between the dominant and non-dominant hands. Patients performed better with their dominant side but this was not statistically significant, due to the small size of the population and the advanced stage of the disease. | NA | NA | NA |
[30] O’Neill M.E. et al. (2016) | Median (IQR) evaluated and compared between right and left side for each parameter and each device, ICC, CIs | Each accelerometer is stable in data collection on both sides, indicating that movement asymmetries may not influence PA measures. Because all 3 accelerometer models exhibited excellent inter-instrument reliability for measuring PA in a variety of real-world activities in TD, it may be appropriate also for CP to wear accelerometers on the right side. | NA | NA | NA |
[37] Coker-Bolt P. et al. (2017) | Active duration, mean activity count, use ratio and magnitude ratio (all based on VM, down-sampled to 1 Hz). | Significant increase in the duration and mean actvity count of affected upper limb use during each camp day and in three of five days in comparison to pre-test data, respectively. No significant changes in all scores pre- vs. post-CIMT. | NA | NA | Upper limb activity when the vector sum activity count > 0. |