Analysis of the characteristics of anticipatory postural adjustments in older adults using smartphones: Association between cognitive and balance functions.

OBJECTIVES: Using smartphones, we aimed to clarify the characteristics of anticipatory postural adjustments (APA) in older adults and examine the relationship between cognitive and balance functions. METHODS: The study participants were 10 young and 13 older adults. An accelerometer built into a smartphone was attached to the lower back (L5) of the participant, and acceleration in the mediolateral direction was measured using a one-leg stance (OLS). As APA features, we analyzed the time to the peak value in the stance direction (peak latency [PL]) and the amount of displacement to the peak value in the stance direction (peak magnitude [PM]). Additionally, the measured PL was divided by PM for each group to obtain the APA ratio (APAr). We investigated the relationship between the APAr and Mini-BESTest subitems. RESULTS: Older adults showed delayed PL and decreased PM levels (p < 0.01). While in the Mini-BESTest sub-items, deductions were most common in the order of dual-task and single-leg standing, and most participants with low APAr scores were degraded in APA of sub-items. The correlation was observed between APAr and both TUG and dual-task cost (DTC) (r= -0.56, r= -0.67). According to the receiver operating characteristic curve, the APAr value was 1.71 in the older age group. CONCLUSIONS: Older adults showed delayed PL and decreased PM, and APAr was associated with cognitive and locomotor functions. By evaluating the APAr at the initiation of movement, it may be possible to distinguish the APA of the older adluts from the possible to the impossible of OLS movement.

New quantitative evaluation of anticipatory postural adjustments using a smartphone in patients with Parkinson's disease.

OBJECTIVE: To investigate a smartphone-enabled quantitative evaluation of anticipatory postural adjustments (APA) during one-leg stance (OLS) movements among individuals with Parkinson's disease (PD). METHODS: This cross-sectional study included 10 young controls, 10 older individuals, and 13 individuals with PD. A smartphone and accelerometer were attached to the participants' lower back (L5), and the movements of the lower back toward the stance side during OLS were measured. For acceleration, the time to the peak value in the stance direction (peak latency [PL]) and the amount of displacement to the peak value in the stance direction (peak magnitude [PM]) were analyzed as APA characteristics. Additionally, the measured PL was divided by the PM for each group to obtain the APA ratio (APAr) as a new index. RESULTS: Individuals with PD showed a delayed PL and decreased PM (vs. young controls: p = .002 for PL, p < .001 for PM) (vs. older individuals: p = .022 for PL, p = .001 for PM). The APAr clustered the young controls, older individuals, and individuals with PD. According to the receiver operating characteristic curve the APAr value was 0.95, and individuals in the PD group were identified (i.e. area under the curve: 0.98; sensitivity: 85.0%; specificity: 100%). Moreover the APAr was correlated with severity and balance ability in individuals with PD (p = .015 for NFOG-Q, p = .028 for UPDRS, p = .036 for TUG, p = .015 for Mini-BESTest, p = .018 for OLS time). CONCLUSIONS: This smartphone-based evaluation using the APAr index was reflective of disease severity and decreased balance ability among individuals with PD. The facilitation of this measurement can help clinicians and physiotherapists quantitatively evaluate the APA of individuals with PD at laboratories and hospitals as well as in home environments.

Clarify Sit-to-Stand Muscle Synergy and Tension Changes in Subacute Stroke Rehabilitation by Musculoskeletal Modeling.

Post-stroke patients exhibit distinct muscle activation electromyography (EMG) features in sit-to-stand (STS) due to motor deficiency. Muscle activation amplitude, related to muscle tension and muscle synergy activation levels, is one of the defining EMG features that reflects post-stroke motor functioning and motor impairment. Although some qualitative findings are available, it is not clear if and how muscle activation amplitude-related biomechanical attributes may quantitatively reflect during subacute stroke rehabilitation. To better enable a longitudinal investigation into a patient's muscle activation changes during rehabilitation or an inter-subject comparison, EMG normalization is usually applied. However, current normalization methods using maximum voluntary contraction (MVC) or within-task peak/mean EMG may not be feasible when MVC cannot be obtained from stroke survivors due to motor paralysis and the subject of comparison is EMG amplitude. Here, focusing on the paretic side, we first propose a novel, joint torque-based normalization method that incorporates musculoskeletal modeling, forward dynamics simulation, and mathematical optimization. Next, upon method validation, we apply it to quantify changes in muscle tension and muscle synergy activation levels in STS motor control units for patients in subacute stroke rehabilitation. The novel method was validated against MVC-normalized EMG data from eight healthy participants, and it retained muscle activation amplitude differences for inter- and intra-subject comparisons. The proposed joint torque-based method was also compared with the common static optimization based on squared muscle activation and showed higher simulation accuracy overall. Serial STS measurements were conducted with four post-stroke patients during their subacute rehabilitation stay (137 ± 22 days) in the hospital. Quantitative results of patients suggest that maximum muscle tension and activation level of muscle synergy temporal patterns may reflect the effectiveness of subacute stroke rehabilitation. A quality comparison between muscle synergies computed with the conventional within-task peak/mean EMG normalization and our proposed method showed that the conventional was prone to activation amplitude overestimation and underestimation. The contributed method and findings help recapitulate and understand the post-stroke motor recovery process, which may facilitate developing more effective rehabilitation strategies for future stroke survivors.

Organization of functional modularity in sitting balance response and gait performance after stroke.

BACKGROUND: Recovery of postural adjustment, especially when seated, is important for performing activities of daily living after stroke. However, conventional clinical measures provide little insight into a common strategy for dynamic sitting balance and gait. We aimed to evaluate functional re-organization of posture and ambulatory performance after stroke. METHODS: The subjects of the study included 5 healthy men and 21 post-stroke patients. The spatiotemporal modular organization of ground reaction forces during a balance task in which the leg on the non-affected side was lifted off the ground while seated was quantified by using complex principal component analysis. FINDINGS: A 3% decrease in the temporal strength of the primary module in post-stroke patients was an independent predictor of gait performance in the hospital setting with high sensitivity and specificity. Tuning of the temporal strength was accompanied by the recovery of sitting and ambulation. INTERPRETATION: Our findings suggest that evaluation of the modular characteristics of ground reaction forces during a sitting balance task allows us to predict recovery and functional adaptation through daily physical rehabilitation.

Spatiotemporal modular organization of muscle torques for sit-to-stand movements.

The robustness of movement patterns is an essential factor for characterizing the adaptability of our daily motions; however, details of the mechanism underlying adaptive motion patterns are not well understood. Here, we utilized complex principal component analysis (CPCA) to examine the spatiotemporal structure of dynamic muscle torques during sit-to-stand (STS) movements. The motion of a three-link rigid body model in the sagittal plane was captured by a Vicon motion analysis system to compute the kinematics of the center of mass (COM), angular displacement, and joint torques. Using CPCA, dynamic muscle torques were decomposed into three components: a control signal, the phase lags of the joint torques, and weighting coefficients. Two kinetic modules were identified in STS, indicating spatiotemporal modular control of the COM in the horizontal and vertical directions. Simulation results suggested that fine-tuning of these two modules according to environmental conditions contributes to adaptive changes in motion pattern. Taken together, our findings suggest that the sources of behavioral adaptations to the environment include the use of fixed modules to reduce computational load on the central nervous system, fine-tuning of these modules, and control of the temporal signals that activate them.

Dynamic optimization of the sit-to-stand movement.

The purpose of this study was to clarify criteria that can predict trajectories during the sit-to-stand movement. In particular, the minimum jerk and minimum torque-change models were examined. Three patterns of sit-to-stand movement from a chair, i.e., upright, natural, and leaning forward, were measured in five young participants using a 3-D motion analysis device (200 Hz). The trajectory of the center of mass and its smoothness were examined, and the optimal trajectories predicted by both models were evaluated. Trajectories of the center of mass predicted by the minimum torque-change model, rather than the minimum jerk model, resembled the measured movements in all rising movement patterns. The upright pattern required greater extension torque of the knee and ankle joints at the instant of seat-off. The leaning-forward pattern required greater extension hip torque and higher movement cost than the natural and upright patterns. These results indicate that the natural sit-to-stand movement might be a result of dynamic optimization.