Primary Image

Mini BEST

Mini Balance Evaluation Systems Test

Last Updated

Purpose

This clinical balance assessment tool is a shortened version of the Balance Evaluation Systems Test (BESTest). It aims to target and identify 6 different balance control systems so that specific rehabilitation approaches can be designed for different balance deficits. The BESTest was shortened based on factor analysis to include dynamic balance only and to improve clinical utilization.

Link to Instrument

Instrument Details

Acronym Mini BESTest

Area of Assessment

Balance – Vestibular
Balance – Non-vestibular
Functional Mobility
Gait
Vestibular

Assessment Type

Performance Measure

Administration Mode

Paper & Pencil

Cost

Free

Diagnosis/Conditions

  • Brain Injury
  • Multiple Sclerosis
  • Parkinson's Disease + Neurologic Rehabilitation
  • Stroke Recovery
  • Vestibular Disorders

Key Descriptions

  • The Mini BESTest is a 14-item test scored on a 3-level ordinal scale.
  • Mini BESTest assesses dynamic balance, a unidimensinal construct and includes 14 items addressing 4 of the 6 sections of the original BESTest:
    1) Anticipatory postural adjustments
    2) Reactive postural control
    3) Sensory orientation
    4) Dynamic gait
  • Notes about scoring:
    1) The original BESTest 4 level (0 - 3) scoring was revised to 3 levels (0 - 2) due to redundancy.
    2) Total score = 28 points per test directions.
    3) Two items have right and left assessment in which the lower score is used within the total score (directions specify which to use).
    4) For research, many studies specify use of both left and right data, thus calculating data based on 32 (vs. 28) points.
  • The revised version of BESTest is based on psychometric properties of items, item scoring, and Rasch analysis designed to improve the measurement qualities of the original test.
  • Scoring definitions and test form available at Horak’s BESTest training website: http://www.bestest.us

    The Mini-BESTest was developed in 2010 by Franchignoni et al.
  • Please see BESTest.us for more informaiton

Number of Items

14

Equipment Required

  • 60 cm x 60 cm block of 4" medium density Tempur foam (T41)
  • Incline ramp of 10 degree slope (2 x 2 foot recommended)
  • Standard chair without arm rests or wheels
  • Firm chair with arms Box that is 9 inches (23 cm) in height (~2 stacked shoeboxes)
  • Stopwatch
  • Masking tape marked on floor at 3 meters from front of chair

Time to Administer

10-15 minutes

Required Training

Reading an Article/Manual

Age Ranges

Adult

18 - 64

years

Elderly Adult

65 +

years

Instrument Reviewers

Cathy Harro MS PT, NCS & the PD EDGE Task Force of the Neurology Section of the APTA; Updated byDiane Wrisley, PT, PhD, NCS and Elizabeth Dannenbaum, MScPT for APTA Neurology Section Vestibular EDGE taskforce.

ICF Domain

Body Function
Activity

Measurement Domain

Motor
Sensory

Professional Association Recommendation

Recommendations for use of the instrument from the Neurology Section of the American Physical Therapy Association’s Multiple Sclerosis Taskforce (MSEDGE), Parkinson’s Taskforce (PD EDGE), Spinal Cord Injury Taskforce (PD EDGE), Stroke Taskforce (StrokEDGE), Traumatic Brain Injury Taskforce (TBI EDGE), and Vestibular Taskforce (Vestibular EDGE) are listed below. These recommendations were developed by a panel of research and clinical experts using a modified Delphi process.

For detailed information about how recommendations were made, please visit:  http://www.neuropt.org/go/healthcare-professionals/neurology-section-outcome-measures-recommendations

Abbreviations:

 

HR

Highly Recommend

R

Recommend

LS / UR

Reasonable to use, but limited study in target group  / Unable to Recommend

NR

Not Recommended

Recommendations for use based on acuity level of the patient:

 

Acute

(CVA < 2 months post)

(SCI < 1 month post) 

(Vestibular < 6 weeks post)

Subacute

(CVA 2 to 6 months)

(SCI 3 to 6 months)

Chronic

(> 6 months)

(Vestibular > 6 weeks post)

Vestibular EDGE

LS

 

LS

Recommendations Based on Parkinson Disease Hoehn and Yahr stage: 

 

I

II

III

IV

V

PD EDGE

HR

HR

HR

HR

NR

Recommendations based on vestibular diagnosis

 

Peripheral

Central

Benign Paroxysmal Positional Vertigo (BPPV)

Other

Vestibular EDGE

LS

LS

LS

LS

Recommendations for entry-level physical therapy education and use in research:

 

Students should learn to administer this tool? (Y/N)

Students should be exposed to tool? (Y/N)

Appropriate for use in intervention research studies? (Y/N)

Is additional research warranted for this tool (Y/N)

PD EDGE

Yes

Yes

Yes

Not reported

Vestibular EDGE

Yes

Yes

Yes

Yes

Considerations

The Mini-BESTest appears to have strong test psychometrics across neurologic populations with good clinical utility as a revised version of BESTest. One discrepancy noted across research however, was the total score (28 vs. 32 points) which depended on whether researchers counted both right/left sides on two test items. Note: original test published standards and instructions, state to count the lowest score of the two sides. See King & Horak, Phys Ther 2013 for a clarification on test scoring.

Do you see an error or have a suggestion for this instrument summary? Please e-mail us!

Vestibular Disorders

back to Populations

Standard Error of Measurement (SEM)

Balance Disorders: 

(Godi, et al, 2013; n = 93 patients with balance disorders, mean age = 66.2(13.2) years, 53 female/40 male, Dxn = 3 Parkinson’s, n = 25 hemiplegia, n = 6 MS, n = 5 vestibular disorders, n = 4 neoplasm CNS, n = 6 neuromuscular disease, n = 8 hereditary ataxia, n = 8 poly neuropathy, n = 6 age-related balance disorders) 

  • SEM = 1.26 (1.01-1.65)

Minimal Detectable Change (MDC)

Balance Disorders: 

(Godi, et al, 2013) 

  • MDC-95 = 3.5

 

Minimally Clinically Important Difference (MCID)

Balance Disorders: 

(Godi,et al, 2013) 

  • Clinically meaningful change is improvement of 4 points (out of 28 total)

Test/Retest Reliability

Balance Disorders:

(Godi, et al, 2013; n = 32 patients with balance disorders, mean age = 67.3 (13.5) years, 19 female/13male, Dx: n = 8 Parkinson’s, n = 7 hemiplegia, n = 3 vestibular disorders, n = 4 age-related balance disorders, 10 with “other neuro" Dx) 

  • Test-retest 1 to 3 days after baseline assessment. Excellent test-retest reliability ICC = 0.96 (0.94-0.99) 

 

Interrater/Intrarater Reliability

Balance Disorders:  

(Godi, et al., 2013; n = 32 patients, sample per above) 

  • Excellent interrater reliability ICC = 0.98 (0.97-0.99) 

 

Internal Consistency

Balance Disorders:

(Franchignoni, et al. 2010; n = 115, mean age = 62.7 (16) years, 62 female/53 male, Dx: = 21 Parkinson’s, n = 15 neuromuscular disease, = 14 hereditary ataxia, = 11 MS, = 22 hemiparesis, = 7 peripheral vestibular disorders, = 6 TBI, = 10 nonspecific age-related balance disorders, = 3 encephalopathy, = 3 cervical myelopathy, = 2 CNS neoplasm) 

  • Factor and Rasch analysis performed to identify optimal test psychometrics for item selection for Mini BESTest. High item separation reliability r = 0.98, Item separation index = 7.35, and Person separation reliability = 0.86 without item redundancy. 

 

(Godi, et al., 2013; n = 93 patients with balance disorders, mean age = 66.2 (13.2)years, 53 female/40male, Dxn = 3 Parkinson’s, n = 25 hemiplegia, n = 6 MS, n = 5 vestibular disorders, n = 4 neoplasm CNS, n = 6 neuromuscular disease, n = 8 hereditary ataxia, n = 8 poly neuropathy, n = 6 age-related balance disorders} 

  • Excellent internal consistency at baseline testing and follow-up assessment: Cronbach alpha = 0.90 and 0.91 respectively
 

 

Criterion Validity (Predictive/Concurrent)

Balance Disorders:

(Godi, et al., 2013) 

  • Excellent concurrent validity of Mini-BESTest with Berg Balance Scale r = 0.85 (CI 0.78-0.90); 
  • Excellent validity between Mini-BESTest and mean global rating of change score in rehabilitation = 0.72 (CI 0.61-0.81)

Construct Validity

Adult with Balance Deficits

(Franchignoni, et al., 2010) 

  • Internal construct validity supported based on hierarchy of item difficulty (Rasch analysis. Item difficulty ranged from -4 to +2.5 logits)

Content Validity

Adults with Balance Deficits

(Franchignoni, et al., 2010; = 115 with diverse neurological diagnoses, 53 men, mean age 62.7 ± 16 years, diagnoses included hemiparesis, Parkinson disease, neuromuscular diseases, hereditary ataxia, multiple sclerosis, peripheral vestibular disorders, traumatic brain injury, cervical myelopathy) 

  • High content validity since individual items are part of well know balance batteries, such as Berg Balance Scale, Clinical Test of Sensory Integration in Balance, Dynamic Gait Index and TUG. 
  • Factor analysis selected 24 out of the 36 original BESTest items likely to represent dynamic balance; Rasch analysis was used to improve rating categories and to delete 10 items that were misfitting or showed local dependency.  The model was verified using confirmatory factor analysis

Face Validity

  • Supported based on balance performance items that examine the construct of dynamic balance.

Floor/Ceiling Effects

Balance Disorders:

(Godi, et al., 2013) 

  • No evidence of floor or ceiling effect in mixed neurologic cohort at baseline mean score = 12.8 (6.9); or after treatment in rehabilitation center mean score = 15.8 (6.9); 2 participants (2.1%) reached Mini BESTest top score.

Responsiveness

Balance Disorders : 

(Godi, et al., 2012; n = 93 patients with balance disorders) 

  • Subjects had 10 physical therapy treatment sessions for balance disorders. 
  • SEM = 1.26 (1.01-1.65); MDC = 3.5 ; MCID = 4 pts; Out of 40 subjects who global rating of change was > 3 (moderate to large improvement) 38/40 (95%) showed Mini-BESTest changes score > 4 pts 
  • Excellent ability to identify those subjects with clinically meaningful improvement: AUC = 0.92 (0.84-0.97), sensitivity = 94%, specificity = 81%, discriminative accuracy to detect moderate improvement in balance = 79%
  • Discriminatory accuracy excellent, area under ROC curve 0.92, to determine a moderate to large global rating of change improvement.

Stroke

back to Populations

Cut-Off Scores

Chronic Stroke 

(Tsang et al 2013, n = 106 people with stroke, mean age 57.1 ± 11.0 years, 73 men, 33 women and 48 controls, mean age 60.2 ± 9.3 years, 28 men and 20 women)

  • Scores of ≤ 17.5 identified those with a history of falling, sensitivity 64%, specificity 64% AUC 0.64

Test/Retest Reliability

Chronic Stroke

(Tsang et al, 2013)

  • Excellent for total score ICC = 0.96, Poor to excellent reliability for individual items kappa = 0.37 to 1.0

 

Interrater/Intrarater Reliability

Chronic Stroke 

(Tsang et al 2013)

  • Excellent for total scores ICC = 0.96, poor to excellent reliability for individual items kappa = 0.36 to 1.0

 

Internal Consistency

Chronic Stroke 

(Tsang et al 2013)

  • Excellent Cronbach’s alpha = 0.89, 0.93, 0.94 for each rater

Criterion Validity (Predictive/Concurrent)

Chronic Stroke

(Tsang et al 2013) 

  • Excellent correlation with Berg Balance Scale r = 0.83
  • Adequate correlation with Functional reach test r = 0.55
  • Excellent correlation with one leg stand on paretic side r = 0.83
  • Adequate correlation with one leg stand on non-paretic side r = 0.54
  • Excellent correlation with Timed “Up & Go” r = -0.82

(Bergstrom et al 2012, n = 9, mean age 78.4 years, range 66-90 years, median 17 months post CVA.  Swedish version)

  • Excellent correlation with Berg Balance Scale r = 0.94
  • Excellent correlation with Timed “Up & Go” r = -0.89

Construct Validity

Chronic Stroke 

(Tsang et al 2013)

  • The mini-BESTest discriminates between those with a history of stroke and healthy control subjects (p < 0.001)
  • The mini-BESTest discriminates between subjects with chronic stroke with and without a history of falling (p = 0.03)

 

Floor/Ceiling Effects

Chronic Stroke 

(Tsang et al 2013)

  • Skewness = - 0.81
  • Floor effect: 0 participants with lowest score
  • Ceiling effect: 0.9% participants with highest score

Parkinson's Disease

back to Populations

Standard Error of Measurement (SEM)

Parkinson’s Disease: 

(Leddy et al, 2011, subset of 24 subjects, MDS-UPDRS = 71 ± 21.9, disease duration = 6.9 ± 3.38; Hoehn and Yahr stage 1 – 2 participants, stage 2 – 11 participants, stage 2.5 – 6 participants, stage 3 – 3 participants, stage 4 – 2 participants, 21% were classified as fallers.)

  • SEM calculated = 6.16% or 1.99 points

Minimal Detectable Change (MDC)

Parkinson’s Disease: 

(Leddy et al, 2011)

  • MDC calculated = 17.1% or 5.52 points

Cut-Off Scores

Parkinson’s Disease:

(Leddy, et al, 2011; total sample n = 80, mean age = 68.2 (9.3)years, mean H & Y = 2.4 (0.64), 31% were fallers) 

  • Preferred Fall risk cut score 63% (20/32 points total) had adequate ability to identify fallers (sensitivity = 0.88, specificity = 0.78). To maximize sensitivity and LR-, a cut score of 72% (23/32) was identified (sensitivity = 0.96, specificity = 0.47) 

 

(Duncan, Leddy, & Earhart, 2013; n =56 with idiopathic PD, mean age = 69.5 years, 32 male/23 female, H&Y stage (2 = 21, 2.5 = 25, 3 = 9, 4 = 1) mean stage 2.4 (0.5)) 

  • Using a cut score of 16/32 points, the Mini-BESTest demonstrated adequate ability to predict 6-month prospective fallers (AUC = 0.80, sensitivity = 0.75, specificity = 0.79, LR+ = 3.57, LR- = 0.32). Mini-BESTest was superior to gait measures to detect fall risk in PD cohort. 

 

(Duncan,et al, 2012; Baseline n = 80 PD, Six-month evaluation n = 51, mean age = 67.5 (8.8), years post diagnosis 7.7(3.9), H & Y stage 2.4 (0.6), UPDRS 37.8 (13.1), 27% fallers; 12-month evaluation n = 40, mean age 67.3 (9.5), years post diagnosis 7.2 (4.1), H&Y stage 2.3 (0.6), UPDRS 39.3 (13.3), 37% fallers) 

Based on a Cut Score < 20/32 points total (63%); 

  • Adequate ability to predict fallers at 6 month prospectively (AUC = 0.87, sensitivity = 0.86, specificity = 0.78, LR+ = 3.97, LR- = 0.18) 
  • Adequate ability to predict fallers at 12 months prospectively (AUC = 0.77, sensitivity = 0.62, specificity = 0.74, LR+ = 2.37, LR- = 0.52) 

 

(Duncan, et al, 2013; n = 80 with idiopathic PD, mean age = 68.2 (9.7), mean MDS-UPDRS 41.3 (14.7), H & Y stage [1 = 4, 2 = 27, 2.5 = 30, 3= 13, 4= 6]) 

Based on a recommended Cut score < 20/32 points to detect fallers: 

  • Adequate ability to identify fallers based on retrospective fall report (AUC = 0.86, sensitivity = 0.88, specificity = 0.78, LR+ = 4.03, LR- = 0.15} 
  • Adequate ability to predictive fallers based on 6 –month prospective falls (AUC = 0.87, sensitivity = 0.86, specificity = 0.78, LR+ = 3.97, LR- = 0.18); and for 12 month prospective falls (AUC = 0.77, sensitivity = 0.62, specificity = 0.74, LR+ = 2.37, LR- = 0.52) 

 

(Mak and Auyeung 2013, n = 110, non-recurrent fallers n=86, 34 female, mean age 63.5± 9.3; recurrent fallers n=24, 10 female, mean age 62.2 ± 7.5)

  • Scores of ≤ 19 identified recurrent fallers; sensitivity 79%, specificity 67% AUC 0.75

 

(King et al 2012)

  • Scores of ≤ 21 differentiate those with and without postural response deficits with a sensitivity of 89%, specificity 81%

Test/Retest Reliability

Parkinson’s Disease:

(Leddy et al, 2011; subset of subjects n = 24, MDS-UPDRS = 71 (21.9), disease duration mean 6.9 (3.38), 21% fallers; H & Y stages [1 = 2, 2 = 11, 2.5 = 6, 3 = 3, 4 = 2], 21% n = 5 fallers) 

  • Excellent test retest reliability (ICC = 0.92)

Interrater/Intrarater Reliability

Parkinson’s Disease:

(Leddy, et al., 2011; subset of subjects, n = 15 MDS-UPDRS = 74.2 (18.6), disease duration = 6.8 years (3.26), H & Y stages (1 = 2, 2 = 7, 2.5 = 3, 3 = 2, 4 = 1), 20% fallers) 

  • Excellent Inter-rater reliability (ICC = 0.91)

Criterion Validity (Predictive/Concurrent)

Parkinson's Disease:

(King, et al., 2012; n = 97, mean age 65.6 (7.1, time since diagnosis mean = 6.5 (5), H & Y mean = 2.3 (0.6) stages 1-4, UPDRS mean = 31.6 (11.2), 59 male/38 female.) 

  • Excellent concurrent validity between Mini-BESTest and Berg (r = 0.79); 
  • Adequate correlation between Mini-BESTest and UPDRS-disease severity (r = -0.51). 

 

(Leddy, et al., 2011; total sample n = 80, mean age = 68.2 (9.3) years, mean H & Y = 2.4 (0.64), 31% were fallers) 

  • Mini-BESTest has excellent correlation with BESTest (= 0.955) 

 

(Duncan, et al., 2013; n = 80 with idiopathic PD, mean age = 68.2 (9.7), mean MDS-UPDRS 41.3 (14.7), H & Y stage [1 = 4, 2 = 27, 2.5 = 30, 3 = 13, 4 = 6]) 

  • Excellent concurrent validity between the Mini-BESTest and Brief BESTest (r = 0.94) 

 

(McNeely, et al., 2012; n = 22, mean age = 71.3 (7.6), 13 male/9 female, MMSE mean 28 (1.8), disease duration mean 7.0 (4.2) years, mean MED_UPDRS = 39.1 (9.2) off meds, 25.3 (6.9) on meds, mean H & Y stage 2.2 (0.3) 

  • Excellent concurrent validity between Mini-BESTest and Berg Balance Scale (r = 0.83); 
  • Adequate correlation between Mini-BESTest and Activity Specific Balance Confidence Scale ABC (r = 0.66). 

 

(McNeely, et al., 2011; n = 23 mean age = 62 (9), mean disease duration = 15 (6) years) 

  • Adequate correlation between Mini-BESTest scores and UPDRS postural stability item (item 3.12) (r = -0.44), p < 0.001

 

(Duncan, et al., 2013; total n = 53, Off meds group n = 28: mean age = 70 (7.4) years, 15 males/13 females, H &Y stage 2 = 8, 2.5 = 15, 3 = 5, 3 fallers & 5 gait freezers; On meds group n = 53, mean age = 68 (8.5) years, 31 males/22 females, H&Y 1 = 2, 2 = 28, 2.5 = 16, 3 = 2, 4 = 5, 11 fallers and 17 gait freezers) 

  • Excellent concurrent validity between Mini-BESTest and Four square step test (r = -0.65) p < 0.001  
  • Mini-Best had adequate predictive validity to discriminate fallers and nonfallers with PD (AUC = 0.80, sensitivity = 0.88, specificity = 0.78); superior to 4SSS for identifying fall risk in PD. 

 

(Duncan, Leddy & Earhart, 2011; n = 80 with idiopathic PD, H & Y stages I-IV, age > 40 years, no details on sample) 

  • Excellent correlation between Mini-BESTest and Five times sit to stand test (r = -0.71 p < 0.001)
  • Multiple regression revealed that Mini-BESTest and Nine Hole peg test explained 53% of variance in FTSTS
 

(Bergstrom et al 2012, n = 9 with mild to moderate Parkinson disease, mean age 60.3 years, age range 46-85 years, 8 female, Hoehn and Yahr stages I-III)

  • Excellent correlation with  Berg Balance Scale r = 0.94
  • Excellent correlation with Timed “Up & Go” r = -0.81
  • Poor correlation with Falls Efficacy Scale r = 0.26

 

(Mak and Auyeung 2013)

  • The mini-BESTest score was a significant predictor of recurrent falls using multivariate logistic regression.

Construct Validity

Parkinson’s Disease:

(Leddy, et al., 2011; total sample n = 80, mean age = 68.2 (9.3) years, mean H & Y = 2.4 (0.64), 31% were fallers) 

  • Significant difference between mean Mini BESTest score of fallers= 14.3 (6.2) and nonfallers = 22.9 (5.5) in PD cohort (average difference between groups of 27%)
  • Total mini-BESTest scores discriminated between fallers and non-fallers AUC = 0.86
  • No specific section of the BESTest or mini-BESTest captured the primary balance deficit

 

(King, et al., 2012; n = 97 see above) 

  • Excellent ability to detect those PD patients with balance deficits based on H & Y stages 1 - 2 versus 3 - 4; AUC = 0.91; Cut off score to distinguish those with and without balance deficits < 21/28 total pts (sensitivity = 89%, specificity = 81%) Mini- BESTest was superior to Berg in discriminating disease severity in PD cohort based on H & Y stage.

Floor/Ceiling Effects

Parkinson's Disease

(King, et al., 2012; = 97, see above) 

  • No evidence of ceiling effect, normal distribution of scores in PD cohort with varied H&Y stages, disease severity.
  • Skewness -0.93 

 

(McNeely, et al., 2012; n = 22, see above) 

  • No ceiling effect was seen in Mini BESTest scores for PD cohort as compared to ceiling effect seen in Berg scores.

 

(Bergstom et al., 2012)

  • no subjects scored the maximum or minimu on the mini-BESTest

Bibliography

Bergstrom, M., Lenholm, E., et al. (2012). "Translation and validation of the Swedish version of the mini-BESTest in subjects with Parkinson's disease or stroke: a pilot study." Physiother Theory Pract 28(7): 509-514. Find it on PubMed

Duncan, R. P. and Earhart, G. M. (2012). "Should One Measure Balance or Gait to Best Predict Falls among People with Parkinson Disease?" Parkinsons Dis 2012: 923493. Find it on PubMed

Duncan, R. P. and Earhart, G. M. (2013). "Four square step test performance in people with Parkinson disease." J Neurol Phys Ther 37(1): 2-8. Find it on PubMed

Duncan, R. P., Leddy, A. L., et al. (2012). "Accuracy of fall prediction in Parkinson disease: six-month and 12-month prospective analyses." Parkinsons Dis 2012: 237673. Find it on PubMed

Duncan, R. P., Leddy, A. L., et al. (2013). "Comparative utility of the BESTest, mini-BESTest, and brief-BESTest for predicting falls in individuals with Parkinson disease: a cohort study." Phys Ther 93(4): 542-550. Find it on PubMed

Duncan, R. P., Leddy, A. L., et al. (2011). "Five times sit-to-stand test performance in Parkinson's disease." Arch Phys Med Rehabil 92(9): 1431-1436. Find it on PubMed

Franchignoni, F., Horak, F., et al. (2010). "Using psychometric techniques to improve the Balance Evaluation System’s Test: the mini-BESTest." Journal of rehabilitation medicine: official journal of the UEMS European Board of Physical and Rehabilitation Medicine 42(4): 323.

Godi, M., Franchignoni, F., et al. (2013). "Comparison of reliability, validity, and responsiveness of the mini-BESTest and Berg Balance Scale in patients with balance disorders." Phys Ther 93(2): 158-167. Find it on PubMed

King, L. and Horak, F. (2013). "Letters and Responses: On the Mini-BESTest: Scoring and the Reporting of Total Scores." Phys Ther 93: 571-575.

King, L. A., Priest, K. C., et al. (2012). "Comparing the Mini-BESTest with the Berg Balance Scale to Evaluate Balance Disorders in Parkinson's Disease." Parkinsons Dis 2012: 375419. Find it on PubMed

Leddy, A. L., Crowner, B. E., et al. (2011). "Utility of the Mini-BESTest, BESTest, and BESTest sections for balance assessments in individuals with Parkinson disease." J Neurol Phys Ther 35(2): 90-97. Find it on PubMed

Mak, M. and Auyeung, M. M. (2013). "The mini-BESTest can predict Parkinsonian recurrent fallers: A 6-month prospective study." Journal of rehabilitation medicine: official journal of the UEMS European Board of Physical and Rehabilitation Medicine.

McNeely, M. E., Duncan, R. P., et al. (2012). "Medication improves balance and complex gait performance in Parkinson disease." Gait Posture 36(1): 144-148. Find it on PubMed

McNeely, M. E., Hershey, T., et al. (2011). "Effects of deep brain stimulation of dorsal versus ventral subthalamic nucleus regions on gait and balance in Parkinson's disease." J Neurol Neurosurg Psychiatry 82(11): 1250-1255. Find it on PubMed

Save now, read later.