Accuracy and Reliability of Single-Camera Measurements of Ankle Clonus and Quadriceps Hyperreflexia.

OBJECTIVE: To evaluate the accuracy and reliability of a simple, single-camera smartphone-based method, named the Reflex Tracker (RT) system, for measuring reflex threshold angles related to ankle clonus and quadriceps hyperreflexia. DESIGN: A prospective comparison study using a high-fidelity reference standard was constructed employing a 2 × 2 × 2 factorial design, with factors of rater (tester) type (student and experienced physical therapist), joint (ankle and knee), and repetition (2 per condition). SETTING: This multicenter study was conducted at 4 outpatient rehabilitation clinics. PARTICIPANTS: A convenience sample of 14 individuals with a neurologic condition presented with 20 lower limbs that exhibited ankle clonus and/or quadriceps hyperreflexia and were included in the study. Also participating in the study were 8 student and 8 experienced physical therapist raters (testers) (N=16). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The plantar flexor reflex threshold angle (PFRTA) related to ankle clonus and the quadriceps reflex threshold angle (QRTA) related to quadriceps hyperreflexia were quantified. RESULTS: PFRTA and QRTA results were compared between the smartphone RT method and synchronous 3-dimensional inertial measurement unit (IMU) sensor motion capture. Mean difference (bias) was minimal between RT and IMU measurements for PFRTA (bias≤0.2°) and QRTA (bias≤1.2°). Intrarater reliability for PFRTA ranged from 0.85-0.90 using RT and from 0.85-0.87 using IMU; QRTA ranged from 0.97-0.98 using RT and from 0.96-0.99 using IMU. Intersensor reliability for PFRTA and QRTA was 0.97 and 0.99, respectively. Minimum detectable change for PFRTA ranged from 7.1°- 8.7° and for QRTA ranged from 6.1°-8.3°. CONCLUSIONS: RT performed comparable to IMU for accurate and reliable measurement of PFRTA and QRTA to quantify ankle clonus and quadriceps hyperreflexia in clinical settings.

Rapid algal culture diagnostics for open ponds using multispectral image analysis.

This article presents a multispectral image analysis approach for probing the spectral backscattered irradiance from algal cultures. It was demonstrated how this spectral information can be used to measure algal biomass concentration, detect invasive species, and monitor culture health in real time. To accomplish this, a conventional RGB camera was used as a three band photodetector for imaging cultures of the green alga Chlorella sp. and the cyanobacterium Anabaena variabilis. A novel floating reference platform was placed in the culture, which enhanced the sensitivity of image color intensity to biomass concentration. Correlations were generated between the RGB color vector of culture images and the biomass concentrations for monocultures of each strain. These correlations predicted the biomass concentrations of independently prepared cultures with average errors of 22 and 14%, respectively. Moreover, the difference in spectral signatures between the two strains was exploited to detect the invasion of Chlorella sp. cultures by A. variabilis. Invasion was successfully detected for A. variabilis to Chlorella sp. mass ratios as small as 0.08. Finally, a method was presented for using multispectral imaging to detect thermal stress in A. variabilis. These methods can be extended to field applications to provide delay free process control feedback for efficient operation of large scale algae cultivation systems.

Multispectral image analysis for algal biomass quantification.

This article reports a novel multispectral image processing technique for rapid, noninvasive quantification of biomass concentration in attached and suspended algae cultures. Monitoring the biomass concentration is critical for efficient production of biofuel feedstocks, food supplements, and bioactive chemicals. Particularly, noninvasive and rapid detection techniques can significantly aid in providing delay-free process control feedback in large-scale cultivation platforms. In this technique, three-band spectral images of Anabaena variabilis cultures were acquired and separated into their red, green, and blue components. A correlation between the magnitude of the green component and the areal biomass concentration was generated. The correlation predicted the biomass concentrations of independently prepared attached and suspended cultures with errors of 7 and 15%, respectively, and the effect of varying lighting conditions and background color were investigated. This method can provide necessary feedback for dilution and harvesting strategies to maximize photosynthetic conversion efficiency in large-scale operation.