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Background: Reactive balance responses are critical for fall prevention. Perturbation-based balance training (PBBT) has shown a positive effect in reducing the risk of falls among older adults and persons with Parkinson’s disease. Objective: To explore the effect of a short-term PBBT on reactive balance responses, performance-based measures of balance and gait and balance confidence. Methods: Thirty-four moderate-high functioning, subacute persons with stroke (PwS) (lower extremity Fugl-Meyer score 29.2 ± 4.3; Berg Balance Scale [BBS] score 43.8 ± 9.5, 42.0 ± 18.7 days after stroke onset) hospitalized in a rehabilitation setting were randomly allocated to PBBT (n = 18) and weight shifting and gait training (WS&GT) (n = 16). Both groups received 12 training sessions, 30 minutes each, for a period of 2.5 weeks. PBBT included unexpected balance perturbations during standing and treadmill walking, WS&GT included weight shifting in standing and treadmill walking without perturbations. The main outcome measures, that is, multiple step-threshold and fall-threshold were examined at baseline, immediately postintervention, and about 5 weeks postintervention. The secondary outcome measures, that is, BBS, 6-minute walk test (6MWT), 10-meter walk test (10MWT), and Activity-specific Balance Confidence (ABC) scale were examined at baseline and immediately postintervention. Results: Compared with the WS&GT group, immediately postintervention participants in the PBBT group showed higher multiple-step thresholds in response to forward and backward surface translations (effect size [ES] = 1.07 and ES = 1.10, respectively) and moderate ES in the ABC scale (ES = 0.74). No significant differences were found in fall-threshold, BBS, 6MWT, and 10MWT between the groups. Conclusions: Inclusion of perturbation training during rehabilitation of PwS improved reactive balance and balance confidence.

Phenotyping is the task of measuring plant attributes for analyzing the current state of the plant. In agriculture, phenotyping can be used to make decisions concerning the management of crops, such as the watering policy, or whether to spray for a certain pest. Currently, large scale phenotyping in fields is typically done using manual labor, which is a costly, low throughput process. Researchers often advocate the use of automated systems for phenotyping, relying on the use of sensors for making measurements. The recent rise of low cost, yet reasonably accurate, RGB-D sensors has opened the way for using these sensors in field phenotyping applications. In this paper, we investigate the applicability of four different RGB-D sensors for this task. We conduct an outdoor experiment, measuring plant attribute in various distances and light conditions. Our results show that modern RGB-D sensors, in particular, the Intel D435 sensor, provides a viable tool for close range phenotyping tasks in fields.