Motor Function Relating to the Accuracy of Self-Overestimation Error in Community-Dwelling Older Adults

Association Between Physical Activity and Performance in Skill Learning Among Older Adults Based on Cognitive Function

BACKGROUND/OBJECTIVES

Most older adults experience cognitive and physical functioning problems; however, they require the ability to learn skills in response to age-related or social environmental changes for independent living. This study aimed to clarify the associations between age-related physical activity and performance in skill learning tasks based on cognitive function.

METHODS

Fifty-eight adults participated in this study and were divided into two groups: the control group (aged under 65 years) and older adult group (aged over 65). All the participants performed two-skill learning exercises based on cognitive function. Habitual exercise was measured using an accelerometer and a self-reported questionnaire.

RESULTS

At baseline, the scores on skill tasks were lower in the older adult group than in the control group and were associated with habitual exercise and motor performance. Skill acquisition, observed in both groups, was associated with age and self-reported physical activity. Retention of the acquired skill was not associated with habitual exercise, and it declined significantly in the older group.

CONCLUSIONS

Skill acquisition was maintained regardless of age; however, the ability to retain the acquired skills decreased among the older adults. Habitual physical activity was associated with skill acquisition but not the retention of the acquired skill. Significance/Implications: The study findings highlight the association between habitual exercise and motor skill learning in older adults, providing insight for practitioners in the rehabilitation and health care fields.

Overestimation associated with walking and balance function in individuals diagnosed with a stroke

BACKGROUND

An estimation error is the difference between motor imagery and actual motor time. Previous studies have reported that overestimation (motor imagery time < actual motor time) is related to physical functions in healthy individuals. However, this finding is unclear among individuals diagnosed with a stroke.

OBJECTIVE

We investigated whether overestimation is related to physical function in individuals diagnosed with a stroke.

METHODS

This study included 71 individuals diagnosed with a stroke (mean age, 67.2 ± 13.4 years; mean time since stroke, 68.4 ± 44.7 days). Imagined timed up and go test (iTUGT) was performed to assess the estimation error. First, the iTUGT was performed; subsequently, the TUGT was performed. The estimation error was calculated by subtracting the TUGT from the iTUGT, with two standard deviations (2 SDs) being calculated. Furthermore, patients were classified into appropriate estimation (AE, within ±2 SD) and overestimation (OE, over -2 SD) groups. Both groups were tested using the estimation error, iTUGT, TUGT, Berg Balance Scale (BBS), and Brunnstrom Recovery Stage (BRS). Subsequently, a correlation analysis was performed.

RESULTS

The OE group had a significantly higher estimation error than the AE group (OE: -7.08 ± 6.87 s, AE: -0.29 ± 1.53 s, P < .001). Moreover, the OE group had significantly lower TUGT and BBS than the AE group. The estimation error was correlated with the TUGT, BBS, and lower-limb BRS (ρ = -0.454, 0.431, 0.291, respectively; P < .05).

CONCLUSIONS

Overestimation was associated with TUGT and balance function in individuals diagnosed with a stroke.

Assessment tools and incidence of hospital-associated disability in older adults: a rapid systematic review

Background

During hospitalization older adults have a high risk of developing functional impairments unrelated to the reasons for their admission. This is termed hospital-associated disability (HAD). This systematic review aimed to assess the incidence of HAD in older adults admitted to acute care with two outcomes: firstly in at least one activity of daily living from a set of functional tasks (e.g., Katz Index) and secondly the incidence of functional decline in an individual functional task (e.g., bathing), and to identify any tools or functional tasks used to assess activities of daily living (ADL) in hospitalized older patients.

Methods

A rapid systematic review was performed according to the recommendations of the Cochrane Rapid Reviews Methods Group and reported the data according the PRISMA statement. A literature search was performed in Medline (via Ovid), EMBASE, and Cochrane Central Register of Controlled Trials databases on 26 August 2021. Inclusion criteria: older adults (≥65 years), assessment of individual items of activities of daily living at baseline and discharge. Exclusion criterion: studies investigating a specific condition that could affect functional decline and studies that primarily examined a population with cognitive impairment. The protocol was registered on OSF registries (https://osf.io/9jez4/) identifier: DOI 10.17605/OSF.IO/9JEZ4.

Results

Ten studies were included in the final review. Incidence of HAD (overall score) was 37% (95% CI 0.30-0.43). Insufficient data prevented meta-analysis of the individual items. One study provided sufficient data to calculate incidence, with the following values for patients' self-reported dependencies: 32% for bathing, 27% for dressing, 27% for toileting, 30% for eating and 27% for transferring. The proxy reported the following values for patients' dependencies: 70% for bathing, 66% for dressing, 70% for toileting, 61% for eating and 59% for transferring. The review identified four assessment tools, two sets of tasks, and individual items assessing activities of daily living in such patients.

Conclusions

Incidence of hospital-associated disability in older patients might be overestimated, due to the combination of disease-related disability and hospital-associated disability. The tools used to assess these patients presented some limitations. These results should be interpreted with caution as only one study reported adequate information to assess the HAD incidence. At the item level, the latter was higher when disability was reported by the proxies than when it was reported by patients. This review highlights the lack of systematic reporting of data used to calculate HAD incidence. The methodological quality and the risk of bias in the included studies raised some concerns.

Longitudinal Changes in Motor Estimation Error and Motor Function in Patients with Parkinson's Disease: A Case Report

BACKGROUND AND OBJECTIVES

This report described two cases with clear longitudinal changes in motor estimation error (difference between the motor imagery and motor execution) and their progression and motor and activities of daily living (ADL) function changes in patients with PD.

MATERIALS AND METHODS

Patient 1 was a 68-year-old man (Hoehn and Yahr [H and Y] stage: IV, diagnosed with PD for 11.8 years) and patient 2 was a 68-year-old woman (H and Y stage: II, diagnosed with PD for 9.6 years). Imagined two-step test (iTST), two-step test (TST), and PD-related assessments (Unified Parkinson's Disease Rating Scale [UPDRS], and Freezing of Gait Questionnaire [FOGQ]) were assessed at baseline and after 6 months. Motor estimation error was calculated as the iTST distance minus TST distance.

RESULTS

In patient 1, motor estimation error was greater after 6 months (baseline: 5.7 [4.8%]/after 6 months: 25.7 cm [26.1%]). Moreover, UPDRS and FOGQ total scores deteriorated after 6 months (UPDRS total: 29/34 point, and FOGQ: 9/16 point). Conversely, in patient 2, motor estimation error did not change notably (-3.6 [7.6%]/-2.5 cm [7.0%]), while UPDRS and FOGQ total scores improved after 6 months (UPDRS total: 17/12 point, and FOGQ: 6/1 point).

CONCLUSIONS

This report indicated that greater motor estimation error may be associated with declining motor and ADL function and disease progression in patients with PD.

Estimation Error Consisting of Motor Imagery and Motor Execution in Patients with Stroke

Previous studies demonstrate that the difference between motor imagery and actual tasks (estimation error) is related to cognitive and physical functions and that a large estimation error (LE) is related to motor imagery ability, including cognitive and physical functions in healthy subjects. The purpose of this study investigated whether estimation error is related to physical and cognitive function in patients with stroke. The study included 60 patients with stroke. The Timed Up and Go Test (TUGT) was employed to assess estimation error. First, the imagined TUGT (iTUGT) was performed; thereafter, the actual TUGT was performed. The estimation error was calculated by subtracting TUGT from iTUGT, with conversion to the absolute value. The patients were classified into the small estimation error (SE) and LE groups, with comparisons of various clinical scores (Mini-Mental State Examination, Berg Balance Scale, 10-m walking speed, Brunnstrom Recovery Stage, and Functional Independence Measure). As a result, the estimation error was significantly larger in the LE group than in the SE group. Cognitive function and balance ability were significantly lower in the LE group than in the SE group. In conclusion, the estimation error was related to physical and cognitive functions in patients with stroke.

Relationship between the vividness of motor imagery and physical function in patients with subacute hemiplegic stroke: a cross-sectional preliminary study

PURPOSE

The study aimed to clarify whether the vividness of motor imagery is related to lower limb function and walking ability in patients with hemiplegic stroke.

MATERIALS AND METHODS

The study was a cross-sectional preliminary study. The subjects were 15 patients with hemiplegic stroke. The vividness of motor imagery was assessed using the kinesthetic and visual imagery questionnaire. The kinesthetic imagery (KI) involves the sensation of one's own movement, whereas the visual imagery (VI) involves the imagination of a third-person performing the self-movement. Their physical functions were assessed using the Brunnstrom recovery stage, stroke impairment assessment set, 10-m maximum walking speed test, and functional independence measure. KI and VI were compared using the t test. Correlation analysis was performed between KI or VI and various variables as well as between the motor imagery gap (difference between KI and VI) and various variables.

RESULTS

KI was significantly lower than VI (p < .01). KI was correlated not only with lower limb function (r = 0.68) but also with walking speed (r = -0.64). The motor imagery gap was correlated with hip joint function (r = -0.53).

CONCLUSIONS

KI and motor imagery gap were associated with lower limb function and walking ability.

Prediction of Physical Frailty in Orthogeriatric Patients Using Sensor Insole-Based Gait Analysis and Machine Learning Algorithms: Cross-sectional Study

Background

Assessment of the physical frailty of older patients is of great importance in many medical disciplines to be able to implement individualized therapies. For physical tests, time is usually used as the only objective measure. To record other objective factors, modern wearables offer great potential for generating valid data and integrating the data into medical decision-making.

Objective

The aim of this study was to compare the predictive value of insole data, which were collected during the Timed-Up-and-Go (TUG) test, to the benchmark standard questionnaire for sarcopenia (SARC-F: strength, assistance with walking, rising from a chair, climbing stairs, and falls) and physical assessment (TUG test) for evaluating physical frailty, defined by the Short Physical Performance Battery (SPPB), using machine learning algorithms.

Methods

This cross-sectional study included patients aged >60 years with independent ambulation and no mental or neurological impairment. A comprehensive set of parameters associated with physical frailty were assessed, including body composition, questionnaires (European Quality of Life 5-dimension [EQ 5D 5L], SARC-F), and physical performance tests (SPPB, TUG), along with digital sensor insole gait parameters collected during the TUG test. Physical frailty was defined as an SPPB score≤8. Advanced statistics, including random forest (RF) feature selection and machine learning algorithms (K-nearest neighbor [KNN] and RF) were used to compare the diagnostic value of these parameters to identify patients with physical frailty.

Results

Classified by the SPPB, 23 of the 57 eligible patients were defined as having physical frailty. Several gait parameters were significantly different between the two groups (with and without physical frailty). The area under the receiver operating characteristic curve (AUROC) of the TUG test was superior to that of the SARC-F (0.862 vs 0.639). The recursive feature elimination algorithm identified 9 parameters, 8 of which were digital insole gait parameters. Both the KNN and RF algorithms trained with these parameters resulted in excellent results (AUROC of 0.801 and 0.919, respectively).

Conclusions

A gait analysis based on machine learning algorithms using sensor soles is superior to the SARC-F and the TUG test to identify physical frailty in orthogeriatric patients.