Functional Outcome of Mechanical Alignment in Total Knee Arthroplasty Surgery: A Short-Term Cohort Study at an Indian Tertiary Care Hospital.

Background: In severe arthritis cases, goal of total knee arthroplasty (TKA) management is to attain pain-free joint and restore the overall limb alignment. There are limited short-term studies published from Indian hospitals that investigated the importance of neutral mechanical component alignment in TKA patients. Methods: Retrospective and prospective study was conducted at the Department of orthopaedics, Sancheti Institute for Orthopaedics and Rehabilitation, Pune from June 2020 to September 2022. Enrolled patients were assessed preoperatively and postoperatively using clinical examination, radiological assessment and functional outcomes through the Oxford knee score, Knee society score and VAS score. Results: 204 patients enrolled, and 267 knees were evaluated for the study. Osteoarthritis was the commonest diagnosis (254 knees, 95.13%). Pre-operatively, 92.13% knees were varus, 4.87% valgus and 3% neutral while post-operatively, 51.69% were varus, 16.1% were valgus, and 32.32% were with neutral axis. Majority of patients with a pre-operative neutral axis converted to varus axis (62.5%), while most valgus axis cases preoperatively converted to a neutral axis (53.84%). For pre-operative varus subgroup, the majority patients with < 10° pre-operative axis converted to neutral (41.28%). Majority patients with 10°-20° pre-operative axis remained varus (60.53%) and with > 20° pre-operative axis remained varus (78.26%). Functional outcome parameters were significantly improved at follow-up (P < 0.05). Conclusion: Short-term postoperative functional scores were significantly improved in postoperative cases, with the postoperative alignment of 0° ± 3° relative to the mechanical axis was achieved. Thus, postoperative neutral mechanical alignment of 0° ± 3° can be the standard of care for patients undergoing TKA.

Midterm survivorship and clinical outcome of INDUS knee prosthesis: 5 year followup study.

BACKGROUND: INDUS knee implant has been designed as per the anatomical morphology of the Indian population and has shown good clinical outcome in short term studies. The purpose of the present study was to report the midterm survivorship and clinical outcome of this implant. MATERIALS AND METHODS: Two hundred and twenty three primary total knee arthroplasties in 209 consecutive patients using the INDUS knee prosthesis were prospectively enrolled. There were 145 females (155 knees) and 64 males (68 knees) with a mean age of 69.95 years (range 42-86 years). Annual followup with clinical and radiological examination was conducted, and a survivorship analysis was done using the Kaplan-Meier analysis. RESULTS: Mean followup was 5.8 years (range 5-6.5 years). Eleven patients died while eight were lost to followup and a total of 204 knees were available for followup. The mean knee flexion improved from preoperative 110.4° ± 11.24° (range 60°-130°) to 128.17° ± 8.32° (range 100°-140°) at the final followup. The mean knee score improved from 40.1 ± 10.7 to 90.3 ± 5.34 while the function score improved from 44.35 ± 12.9 to 89.58 ± 7.43. Two patient developed infection and required revision. The Kaplan-Meier analysis reported a survivorship of 98.6% (confidence interval 95.7-99.6%) at the end for 5 years for INDUS knee prosthesis. CONCLUSION: INDUS knee prosthesis has excellent survivorship with a good clinical outcome and low failure rate.

Biomimetic spectro-temporal features for music instrument recognition in isolated notes and solo phrases.

The identity of musical instruments is reflected in the acoustic attributes of musical notes played with them. Recently, it has been argued that these characteristics of musical identity (or timbre) can be best captured through an analysis that encompasses both time and frequency domains; with a focus on the modulations or changes in the signal in the spectrotemporal space. This representation mimics the spectrotemporal receptive field (STRF) analysis believed to underlie processing in the central mammalian auditory system, particularly at the level of primary auditory cortex. How well does this STRF representation capture timbral identity of musical instruments in continuous solo recordings remains unclear. The current work investigates the applicability of the STRF feature space for instrument recognition in solo musical phrases and explores best approaches to leveraging knowledge from isolated musical notes for instrument recognition in solo recordings. The study presents an approach for parsing solo performances into their individual note constituents and adapting back-end classifiers using support vector machines to achieve a generalization of instrument recognition to off-the-shelf, commercially available solo music.

Factors affecting range of motion in total knee arthroplasty using high flexion prosthesis: A prospective study.

BACKGROUND: High flexion implants have been reported to provide better range of motion (ROM). The few studies analyzing the factors affecting the ROM are scarce. This study aims to find the factors that affect ROM when using a high flex knee design (INDUS knee). MATERIALS AND METHODS: Two hundred and fifty three consecutive patients of total knee arthroplasty (TKA) done by using INDUS knee prosthesis between Sept 2008 and Sept 2009 were included in the study. The cases with osteoarthritis (OA) and Rheumatoid arthritis (RA) were included in study. 5 patients were lost to followup and 248 patients (267 knees, 19 bilateral, 221 OA, and 46 RA) were analyzed for the following factors - sex, age, body mass index (BMI), preoperative ROM, flexion deformity, preoperative total knee score and functional score, time of tourniquet release and patella resurfacing. Subgroup classification using above factors was performed and statistical analysis of effect of all the above factors on final knee ROM was done. Assessment was done preoperatively and at 3 months, 6 months and 1 year postoperatively. The final outcome evaluation was done at one year followup. RESULTS: The mean age was 68.2 years (range 40-89 years) with 79 males and 189 females. The mean knee range improved from 97.62 ± 11° to 132 ± 8°. Factors that positively affect ROM of INDUS knee prosthesis at the end of 1 year were preoperative ROM, total knee score and functional score, and diagnosis of osteoarthritis, whereas BMI, preoperative flexion deformity has a negative influence on final flexion at the end of 1 year. Age and gender of the patients, patella resurfacing, and use of two different tourniquet protocols did not affect the final outcome. CONCLUSION: Preoperative ROM and preoperative functional status are the most important factors affecting final range. Patients should be counseled accordingly and made to understand these factors.

Recognizing the message and the messenger: biomimetic spectral analysis for robust speech and speaker recognition.

Humans are quite adept at communicating in presence of noise. However most speech processing systems, like automatic speech and speaker recognition systems, suffer from a significant drop in performance when speech signals are corrupted with unseen background distortions. The proposed work explores the use of a biologically-motivated multi-resolution spectral analysis for speech representation. This approach focuses on the information-rich spectral attributes of speech and presents an intricate yet computationally-efficient analysis of the speech signal by careful choice of model parameters. Further, the approach takes advantage of an information-theoretic analysis of the message and speaker dominant regions in the speech signal, and defines feature representations to address two diverse tasks such as speech and speaker recognition. The proposed analysis surpasses the standard Mel-Frequency Cepstral Coefficients (MFCC), and its enhanced variants (via mean subtraction, variance normalization and time sequence filtering) and yields significant improvements over a state-of-the-art noise robust feature scheme, on both speech and speaker recognition tasks.

A Multistream Feature Framework Based on Bandpass Modulation Filtering for Robust Speech Recognition.

There is strong neurophysiological evidence suggesting that processing of speech signals in the brain happens along parallel paths which encode complementary information in the signal. These parallel streams are organized around a duality of slow vs. fast: Coarse signal dynamics appear to be processed separately from rapidly changing modulations both in the spectral and temporal dimensions. We adapt such duality in a multistream framework for robust speaker-independent phoneme recognition. The scheme presented here centers around a multi-path bandpass modulation analysis of speech sounds with each stream covering an entire range of temporal and spectral modulations. By performing bandpass operations along the spectral and temporal dimensions, the proposed scheme avoids the classic feature explosion problem of previous multistream approaches while maintaining the advantage of parallelism and localized feature analysis. The proposed architecture results in substantial improvements over standard and state-of-the-art feature schemes for phoneme recognition, particularly in presence of nonstationary noise, reverberation and channel distortions.

Music in our ears: the biological bases of musical timbre perception.

Timbre is the attribute of sound that allows humans and other animals to distinguish among different sound sources. Studies based on psychophysical judgments of musical timbre, ecological analyses of sound's physical characteristics as well as machine learning approaches have all suggested that timbre is a multifaceted attribute that invokes both spectral and temporal sound features. Here, we explored the neural underpinnings of musical timbre. We used a neuro-computational framework based on spectro-temporal receptive fields, recorded from over a thousand neurons in the mammalian primary auditory cortex as well as from simulated cortical neurons, augmented with a nonlinear classifier. The model was able to perform robust instrument classification irrespective of pitch and playing style, with an accuracy of 98.7%. Using the same front end, the model was also able to reproduce perceptual distance judgments between timbres as perceived by human listeners. The study demonstrates that joint spectro-temporal features, such as those observed in the mammalian primary auditory cortex, are critical to provide the rich-enough representation necessary to account for perceptual judgments of timbre by human listeners, as well as recognition of musical instruments.

A multiresolution analysis for detection of abnormal lung sounds.

Automated analysis and detection of abnormal lung sound patterns has great potential for improving access to standardized diagnosis of pulmonary diseases, especially in low-resource settings. In the current study, we develop signal processing tools for analysis of paediatric auscultations recorded under non-ideal noisy conditions. The proposed model is based on a biomimetic multi-resolution analysis of the spectro-temporal modulation details in lung sounds. The methodology provides a detailed description of joint spectral and temporal variations in the signal and proves to be more robust than frequency-based techniques in distinguishing crackles and wheezes from normal breathing sounds.